Derivatives of D(-) glutamine-based MMP-2 inhibitors as an effective remedy for the management of chronic myeloid leukemia-Part-I: Synthesis, biological screening and in silico binding interaction analysis.

Chronic myeloid leukemia (CML) is a global issue and the available drugs such as tyrosine kinase inhibitors (TKIs) comprise various toxic effects as well as resistance and cross-resistance. Therefore, novel molecules targeting specific enzymes may unravel a new direction in antileukemic drug discovery. In this context, targeting gelatinases (MMP-2 and MMP-9) can be an alternative option for the development of novel molecules effective against CML. In this article, some D(-)glutamine derivatives were synthesized and evaluated through cell-based antileukemic assays and tested against gelatinases. The lead compounds, i.e., benzyl analogs exerted the most promising antileukemic potential showing nontoxicity in normal cell line including efficacious gelatinase inhibition. Both these lead molecules yielded effective apoptosis and displayed marked reductions in MMP-2 expression in the K562 cell line. Not only that, but both of them also revealed effective antiangiogenic efficacy. Importantly, the most potent MMP-2 inhibitor, i.e., benzyl derivative of p-tosyl D(-)glutamine disclosed stable binding interaction at the MMP-2 active site correlating with the highly effective MMP-2 inhibitory activity. Therefore, such D(-)glutamine derivatives might be explored further as promising MMP-2 inhibitors with efficacious antileukemic profiles for the treatment of CML in the future.

Unraveling HDAC11: Epigenetic orchestra in different diseases and structural insights for inhibitor design.

Histone deacetylase 11 (HDAC11), a member of the HDAC family, has emerged as a critical regulator in numerous physiological as well as pathological processes. Due to its diverse roles, HDAC11 has been a focal point of research in recent times. Different non-selective inhibitors are already approved, and research is going on to find selective HDAC11 inhibitors. The objective of this review is to comprehensively explore the role of HDAC11 as a pivotal regulator in a multitude of physiological and pathological processes. It aims to delve into the intricate details of HDAC11's structural and functional aspects, elucidating its molecular interactions and implications in different disease contexts. With a primary focus on elucidating the structure-activity relationships (SARs) of HDAC11 inhibitors, this review also aims to provide a holistic understanding of how its molecular architecture influences its inhibition. Additionally, by integrating both established knowledge and recent research, the review seeks to contribute novel insights into the potential therapeutic applications of HDAC11 inhibitors. Overall, the scope of this review spans from fundamental research elucidating the complexities of HDAC11 biology to the potential of targeting HDAC11 in therapeutic interventions.

Density functional theory (DFT) studies in HDAC-based chemotherapeutics: Current findings, case studies and future perspectives.

Density Functional Theory (DFT) is a quantum chemical computational method used to predict and analyze the electronic properties of atoms, molecules, and solids based on the density of electrons rather than wavefunctions. It provides insights into the structure, bonding, and behavior of different molecules, including those involved in the development of chemotherapeutic agents, such as histone deacetylase inhibitors (HDACis). HDACs are a wide group of metalloenzymes that facilitate the removal of acetyl groups from acetyl-lysine residues situated in the N-terminal tail of histones. Abnormal HDAC recruitment has been linked to several human diseases, especially cancer. Therefore, it has been recognized as a prospective target for accelerating the development of anticancer therapies. Researchers have studied HDACs and its inhibitors extensively using a combination of experimental methods and diverse in-silico approaches such as machine learning and quantitative structure-activity relationship (QSAR) methods, molecular docking, molecular dynamics, pharmacophore mapping, and more. In this context, DFT studies can make significant contribution by shedding light on the molecular properties, interactions, reaction pathways, transition states, reactivity and mechanisms involved in the development of HDACis. This review attempted to elucidate the scope in which DFT methodologies may be used to enhance our comprehension of the molecular aspects of HDAC inhibitors, aiding in the rational design and optimization of these compounds for therapeutic applications in cancer and other ailments. The insights gained can guide experimental efforts toward developing more potent and selective HDAC inhibitors.

Exploration of Fingerprints and Data Mining-based Prediction of Some Bioactive Compounds from Allium sativum as Histone Deacetylase 9 (HDAC9) Inhibitors.

BACKGROUND: Histone deacetylase 9 (HDAC9) is an important member of the class IIa family of histone deacetylases. It is well established that over-expression of HDAC9 causes various types of cancers including gastric cancer, breast cancer, ovarian cancer, liver cancer, lung cancer, lymphoblastic leukaemia, etc. The important role of HDAC9 is also recognized in the development of bone, cardiac muscles, and innate immunity. Thus, it will be beneficial to find out the important structural attributes of HDAC9 inhibitors for developing selective HDAC9 inhibitors with higher potency. METHODS: The classification QSAR-based methods namely Bayesian classification and recursive partitioning method were applied to a dataset consisting of HADC9 inhibitors. The structural features strongly suggested that sulphur-containing compounds can be a good choice for HDAC9 inhibition. For this reason, these models were applied further to screen some natural compounds from Allium sativum. The screened compounds were further accessed for the ADME properties and docked in the homology-modelled structure of HDAC9 in order to find important amino acids for the interaction. The best-docked compound was considered for molecular dynamics (MD) simulation study. RESULTS: The classification models have identified good and bad fingerprints for HDAC9 inhibition. The screened compounds like ajoene, 1,2 vinyl dithiine, diallyl disulphide and diallyl trisulphide had been identified as compounds having potent HDAC9 inhibitory activity. The results from ADME and molecular docking study of these compounds show the binding interaction inside the active site of the HDAC9. The best-docked compound ajoene shows satisfactory results in terms of different validation parameters of MD simulation study. CONCLUSION: This in-silico modelling study has identified the natural potential lead (s) from Allium sativum. Specifically, the ajoene with the best in-silico features can be considered for further in-vitro and in-vivo investigation to establish as potential HDAC9 inhibitors.

Advances in structure-activity relationships of HDAC inhibitors as HIV latency-reversing agents.

INTRODUCTION: HIV-infected cells may rebound due to the existence of the silent HIV-infected memory CD4+ T cells (HIV latency). This HIV latency makes the disease almost incurable. In latency, the integrated proviral DNA of HIV is transcriptionally silenced partly due to the activity of histone deacetylases (HDACs). Hence, inhibition of HDAC is considered a prime target for HIV latency reversal. AREAS COVERED: A brief biology and function of HDACs have been discussed to identify key points to design HDAC inhibitors (HDACis). This article summarizes recent achievements in the development of HDACis to achieve HIV latency reversal. Structure-activity relationships (SARs) of some series of compounds were also explored. EXPERT OPINION: Depletion of the HIV reservoir is the only way to end this deadly epidemic. HDACis are latency-reversing agents (LRA) that can be used to 'shock' the latently infected CD4+ T cells to induce them to produce viral proteins. It is interesting to note that HDAC3, which is extensively expressed in resting T cells, is specifically preferred by benzamide-containing HDACis for inhibition. Thus, the benzamide class of compounds should be explored. Nevertheless, more data on selective HDAC inhibition is needed for further development of HDACis in HIV latency reversal.

HDAC9 as a Privileged Target: Reviewing its Role in Different Diseases and Structure-activity Relationships (SARs) of its Inhibitors.

HDAC9 is a histone deacetylase enzyme belonging to the class IIa of HDACs which catalyses histone deacetylation. HDAC9 inhibit cell proliferation by repairing DNA, arresting the cell cycle, inducing apoptosis, and altering genetic expression. HDAC9 plays a significant part in human physiological system and are involved in various type of diseases like cancer, diabetes, atherosclerosis and CVD, autoimmune response, inflammatory disease, osteoporosis and liver fibrosis. This review discusses the role of HDAC9 in different diseases and structure-activity relationships (SARs) of various hydroxamate and non-hydroxamate-based inhibitors. SAR of compounds containing several scaffolds have been discussed in detail. Moreover, structural requirements regarding the various components of HDAC9 inhibitor (cap group, linker and zinc-binding group) has been highlighted in this review. Though, HDAC9 is a promising target for the treatment of a number of diseases including cancer, a very few research are available. Thus, this review may provide useful information for designing novel HDAC9 inhibitors to fight against different diseases in the future.

Are inhibitors of histone deacetylase 8 (HDAC8) effective in hematological cancers especially acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL)?

Histone deacetylase 8 (HDAC8) aberrantly deacetylates histone and non-histone proteins. These include structural maintenance of chromosome 3 (SMC3) cohesin protein, retinoic acid induced 1 (RAI1), p53, etc and thus, regulating diverse processes such as leukemic stem cell (LSC) transformation and maintenance. HDAC8, one of the crucial HDACs, affects the gene silencing process in solid and hematological cancer progressions especially on acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). A specific HDAC8 inhibitor PCI-34051 showed promising results against both T-cell lymphoma and AML. Here, we summarize the role of HDAC8 in hematological malignancies, especially in AML and ALL. This article also introduces the structure/function of HDAC8 and a special attention has been paid to address the HDAC8 enzyme selectivity issue in hematological cancer especially against AML and ALL.

Interaction of systemic drugs causing ocular toxicity with organic cation transporter: an artificial intelligence prediction.

Chronic disease patients (cancer, arthritis, cardiovascular diseases) undergo long-term systemic drug treatment. Membrane transporters in ocular barriers could falsely recognize these drugs and allow their trafficking into the eye from systemic circulation. Hence, despite their pharmacological activity, these drugs accumulate and cause toxicity at the non-target site, such as the eye. Since around 40% of clinically used drugs are organic cation in nature, it is essential to understand the role of organic cation transporter (OCT1) in ocular barriers to facilitate the entry of systemic drugs into the eye. We applied machine learning techniques and computer simulation models (molecular dynamics and metadynamics) in the current study to predict the potential OCT1 substrates. Artificial intelligence models were developed using a training dataset of a known substrates and non-substrates of OCT1 and predicted the potential OCT1 substrates from various systemic drugs causing ocular toxicity. Computer simulation studies was performed by developing the OCT1 homology model. Molecular dynamic simulations equilibrated the docked protein-ligand complex. And metadynamics revealed the movement of substrates across the transporter with minimum free energy near the binding pocket. The machine learning model showed an accuracy of about 80% and predicted the potential substrates for OCT1 among systemic drugs causing ocular toxicity - not known earlier, such as cyclophosphamide, bupivacaine, bortezomib, sulphanilamide, tosufloxacin, topiramate, and many more. However, further invitro and invivo studies are required to confirm these predictions.Communicated by Ramaswamy H. Sarma.

Exploring molecular fingerprints of different drugs having bile interaction: a stepping stone towards better drug delivery.

Bile acids are amphiphilic substances produced naturally in humans. In the context of drug delivery and dosage form design, it is critical to understand whether a drug interacts with bile inside the gastrointestinal (GI) tract or not. This study focuses on the identification of structural fingerprints/features important for bile interaction. Molecular modelling methods such as Bayesian classification and recursive partitioning (RP) studies are executed to find important fingerprints/features for the bile interaction. For the Bayesian classification study, the ROC score of 0.837 and 0.950 are found for the training set and the test set compounds, respectively. The fluorine-containing aliphatic/aromatic group, the branched chain of the alkyl group containing hydroxyl moiety and the phenothiazine ring etc. are identified as good fingerprints having a positive contribution towards bile interactions, whereas, the bad fingerprints such as free carboxylate group, purine, and pyrimidine ring etc. have a negative contribution towards bile interactions. The best tree (tree ID: 1) from the RP study classifies the bile interacting or non-interacting compounds with a ROC score of 0.941 for the training and 0.875 for the test set. Additionally, SARpy and QSAR-Co analyses are also been performed to classify compounds as bile interacting/non-interacting. Moreover, forty-six recently FDA-approved drugs have been screened by the developed SARpy and QSAR-Co models to assess their bile interaction properties. Overall, this attempt may facilitate the researchers to identify bile interacting/non-interacting molecules in a faster way and help in the design of formulations and target-specific drug development.

Exploring structural requirements of HDAC10 inhibitors through comparative machine learning approaches.

Histone deacetylase (HDAC) inhibitors are in the limelight of anticancer drug development and research. HDAC10 is one of the class-IIb HDACs, responsible for cancer progression. The search for potent and effective HDAC10 selective inhibitors is going on. However, the absence of human HDAC10 crystal/NMR structure hampers the structure-based drug design of HDAC10 inhibitors. Different ligand-based modeling techniques are the only hope to speed up the inhibitor design. In this study, we applied different ligand-based modeling techniques on a diverse set of HDAC10 inhibitors (n = 484). Machine learning (ML) models were developed that could be used to screen unknown compounds as HDAC10 inhibitors from a large chemical database. Moreover, Bayesian classification and Recursive partitioning models were used to identify the structural fingerprints regulating the HDAC10 inhibitory activity. Additionally, a molecular docking study was performed to understand the binding pattern of the identified structural fingerprints towards the active site of HDAC10. Overall, the modeling insight might offer helpful information for medicinal chemists to design and develop efficient HDAC10 inhibitors.

A review of MMP-2 structures and binding mode analysis of its inhibitors to strategize structure-based drug design.

The protease enzyme, matrix metalloproteinase-2 (MMP-2) has been a target of choice for the drug development due to its multi-façade involvement in numerous diseased conditions including cancer. To find a selective MMP-2 inhibitor several computational strategies are employed in its design and discovery. In these strategies, protein structure of MMP-2 is an inevitable part to formulate effective structure-based drug design (SBDD) of selective MMP-2 inhibitors. In the present communication, several crystal structures of MMP-2 have been analyzed with different statistical parameters and their implementations in SBDD of inhibitors are scrutinized. In addition, binding mode analyses of various classes of inhibitors are discussed to pinpoint the effective design of selective inhibitors by maximizing its interaction with the MMP-2 enzyme binding site. This may provide a crucial insight for exploring the numerous possibilities for SBDD of MMP-2 inhibitors to accelerate anticancer drug discovery efforts.

Recent trends in fragment-based anticancer drug design strategies against different targets: A mini-review.

Cancer is a rapidly growing disease in modern society. Chemotherapy is the first choice for cancer treatment. Design and development of new chemotherapeutic drugs by targeting specific proteins are put down by a high attrition rate at different stages. Fragment-based drug design (FBDD) is one of the successful structure-based drug design processes to avoid attrition-related problems. This review highlighted the computational and experimental FBDD techniques used to design molecules with anticancer properties. This study describes FBBD strategies for different targets like aurora kinase, phosphoinositide-dependent protein kinase-1 (PDK1), signal transducer and activator of transcription 3 (STAT3), myeloid cell leukemia-1 (Mcl-1), tankyrase (TNKS), choline kinase, protein kinase, tyrosine kinase and lysine-specific demethylase 1 (LSD1) which are vital targets for cancer treatments. This review will enrich the scientific community to understand the fragment-based design strategies for finding suitable leads over high throughput screening (HTS) in the future.

Inonotus obliquus aqueous extract prevents histopathological alterations in liver induced by environmental toxicant Microcystin.

Environmental toxicants like microcystins are known to adversely impact liver physiology and lead to the increased risk for abnormal liver function and even liver carcinoma. Chaga mushroom (Inonotus obliquus) is reported for various properties mainly antibacterial, antiallergic, anti-inflammatory, antioxidant, and anticancer properties. This study was aimed to assess the effect microcystin (MC-LR) on histopathology of liver in mice and a preventive measure by using aqueous extract of Inonotus obliquus (IOAE). Adult Balb/c mice were administered with MC-LR at 20 â€‹µg/kg body weight, per day, intraperitoneal (i.p.) for 4 weeks. IOAE was treated to one group of MC-LR mice at 200 â€‹mg/kg body weight, per oral, for 4 weeks. Histological staining for liver structural details and biochemical assays for functions were assessed. The results of the study showed that MC-LR drastically reduced the body weight of mice which were restored close to the range of control by IOAE treatment. MC-LR exposed mice showed 1.9, 1.7 and 2.2-fold increase in the levels of SGOT, SGPT and LDH which were restored by IOAE treatment as compared to control (one-fold). MC-LR exposed mice showed reduced level of GSH (19.83 â€‹± â€‹3.3 â€‹µM) which were regained by IOAE treatment (50.83 â€‹± â€‹3.0 â€‹µM). Similar observations were noted for catalase activity. Histological examinations show that MC-LR exposed degenerative changes in the liver sections which were restored by IOAE supplementation. The immunofluorescence analysis of caspase-3 counterstained with DAPI showed that MC-LR led to the increased expression of caspase-3 which were comparatively reduced by IOAE treatment. The cell viability decreased on increasing the concentration of MC-LR with 5% cell viability at concentration of 10 â€‹µg MC-LR/mL as that of control 100% Cell viability. The IC50 was calculated to be 3.6 â€‹µg/ml, indicating that MC-LR is chronic toxic to AML12 mouse hepatocytes. The molecular docking interaction of NF-κB-NIK with ergosterol peroxidase showed binding interaction between the two and showed the plausible molecular basis for the effects of IOAE in MC-LR induced liver injury. Collectively, this study revealed the deleterious effects of MC-LR on liver through generation of oxidative stress and activation of caspase-3, which were prevented by treatment with IOAE.

Updated chemical scaffolds of ABCG2 inhibitors and their structure-inhibition relationships for future development.

ATP-binding cassette (ABC) transporters are pivotal for cell detoxification and survival. Overexpression of ABC transporter in tumor cells lead to chemoresistance through the efflux of chemotherapeutic agents. P-glycoprotein (Pgp/ABCB1), multidrug resistance protein 1 (MRP1/ABCC1) and breast cancer resistance protein (BCRP/ABCG2) are the major ABC transporters involved in multidrug resistance (MDR) of cancer cells against anticancer drugs. ABCG2 is one of the major transporters involved in the efflux of different cytotoxic agents. Hence, inhibition of ABCG2-mediated transport is considered a prime target to resist MDR of cancer cells. Here, brief structural biology and functions of ABCG2 were discussed with the aim to identify key pharmacophoric elements to design potent and selective as well as non-toxic ABCG2 inhibitors. Structure-inhibition relationships (SIRs) of the earlier reported compounds were also explored. Taken together, this study offers insight for further development of ABCG2 inhibitors.

A critical analysis of urea transporter B inhibitors: molecular fingerprints, pharmacophore features for the development of next-generation diuretics.

Urea transporter is a membrane transport protein. It is involved in the transferring of urea across the cell membrane in humans. Along with urea transporter A, urea transporter B (UT-B) is also responsible for the management of urea concentration and blood pressure of human. The inhibitors of urea transporters have already generated a huge attention to be developed as alternate safe class of diuretic. Unlike conventional diuretics, these inhibitors are suitable for long-term therapy without hampering the precious electrolyte imbalance in the human body. In this study, UT-B inhibitors were analysed by using multi-chemometric modelling approaches. The possible pharmacophore features along with favourable and unfavourable sub-structural fingerprints for UT-B inhibition are extracted. This information will guide the medicinal chemist to design potent UT-B inhibitors in future.

How the structural properties of the indole derivatives are important in kinase targeted drug design?: A case study on tyrosine kinase inhibitors.

Kinases are considered as important signalling enzymes that illustrate 20% of the druggable genome. Human kinase family comprises >500 protein kinases and about 20 lipid kinases. Protein kinases are responsible for the mechanism of protein phosphorylation. These are necessary for regulation of various cellular activities including proliferation, cell cycle, apoptosis, motility, growth, differentiation, etc. Their deregulation leads to disruption of many cellular processes leading to different diseases most importantly cancer. Thus, kinases are considered as valuable targets in different types of cancer as well as other diseases. Researchers around the world are actively engaged in developing inhibitors based on distinct chemical scaffolds. Indole represents as a versatile scaffold in the naturally occurring and bioactive molecules. It is also used as a privileged scaffold for the target-based drug design against different diseases. This present article aim to review the applications of indole scaffold in the design of inhibitors against different tyrosine kinases such as epidermal growth factor receptors (EGFRs), vascular endothelial growth factor receptors (VEGFRs), platelet-derived growth factor receptors (PDGFRs), etc. Important structure activity relationships (SARs) of indole derivatives were discussed. The present work is an attempt to summarize all the crucial structural information which is essential for the development of indole based tyrosine kinase inhibitors with improved potency.

Exploring naphthyl derivatives as SARS-CoV papain-like protease (PLpro) inhibitors and its implications in COVID-19 drug discovery.

Novel coronavirus disease 2019 (COVID-19) emerges as a serious threat to public health globally. The rapid spreading of COVID-19, caused by severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2), proclaimed the multitude of applied research needed not only to save the human health but also for the environmental safety. As per the recent World Health Organization reports, the novel corona virus may never be wiped out completely from the world. In this connection, the inhibitors already designed against different targets of previous human coronavirus (HCoV) infections will be a great starting point for further optimization. Pinpointing biochemical events censorious to the HCoV lifecycle has provided two proteases: a papain-like protease (PLpro) and a 3C-like protease (3CLpro) enzyme essential for viral replication. In this study, naphthyl derivatives inhibiting PLpro enzyme were subjected to robust molecular modelling approaches to understand different structural fingerprints important for the inhibition. Here, we cover two main aspects such as (a) exploration of naphthyl derivatives by classification QSAR analyses to find important fingerprints that module the SARS-CoV PLpro inhibition and (b) implications of naphthyl derivatives against SARS-CoV-2 PLpro enzyme through detailed ligand-receptor interaction analysis. The modelling insights will help in the speedy design of potent broad spectrum PLpro inhibitors against infectious SARS-CoV and SARS-CoV-2 in the future.

Exploring sodium glucose cotransporter (SGLT2) inhibitors with machine learning approach: A novel hope in anti-diabetes drug discovery.

Conventional anti-diabetes agents exhibit some undesirable side effects. Recently, lactic acidosis and/or bladder cancer were also reported with the use of these agents. Hence, there is an urgent need for alternative anti-diabetes in order to reduce/avoid the unwanted effects. In this scenario sodium glucose cotransporter 2 (SGLT2) inhibitors has already been established as an important class of anti-diabetic drug. The search for new generation SGLT2 inhibitors with high affinity is still an ongoing process. Here, we aim to develop computational models to predict the SGLT2 inhibitory activity of small molecules based on chemical structures. This work provides in-silico analysis to propose possible fragment/fingerprint identification recommended for SGLT2 inhibitors. Up-to-our knowledge, this study is an initiative to propose fingerprints responsible for SGLT2 inhibition. Furthermore, we used nine different algorithms to build machine learning (ML) models that could be used to prioritize compounds as SGLT2 inhibitors from large libraries. The best performing ML models were applied to virtually screen a large collection of FDA approved drugs. The best predicted compounds have been recommended to be biologically investigated in future in order to identify next generation SGLT2 inhibitors with different chemical structure.

Urea transporter and its specific and nonspecific inhibitors: State of the art and pharmacological perspective.

Hypertension is a major concern for a wide array of patients. The traditional drugs are commonly referred as 'water pills' and these molecules have been successful in alleviating hypertension. However, this comes at the high expense of precious electrolytes in our body. To dissipate this major adverse effect, the urea transporter inhibitors play especially important roles in maintaining the fluid balance by maintaining the concentration of urea in the inner medullary collecting duct. The purpose of this communication is to provide insights into the structural feature of these target proteins and inhibition of both urea transporter types A (UT-A) and B (UT-B) selectively and non-selectively with a special focus on the UT-A inhibitors as they are the primary target for diuresis. It was observed that a wide class of drugs such as thiourea analogues, 2,7-disubstituted fluorenones can inhibit both the protein non-selectively whereas 8-hydroxyquinoline, aminothiazolone, 1,3,5-triazine, triazolothienopyrimidine, thienoquinoline, arylthiazole, γ-sultambenzosulfonamide and 1,2,4-triazoloquinoxaline classes of compounds inhibit UT-A. The goal of this study is to highlight the important aspects that may be useful to understanding the perspectives of urea transporter inhibitors in rational drug discovery.

Structure and dynamics of sodium alginate as elucidated by chemical shift anisotropy and site-specific spin-lattice relaxation time measurements.

The biocompatible, biodegradable, linear copolymer sodium alginate is fabricated from [Formula: see text] linked [Formula: see text]-D-mannuronic acid (M block) and [Formula: see text]-L-guluronic acid (G-block). It has wide applications in drug delivery, cell encapsulation, and commercial application in the textile, cosmetics, paper, food, biomedical, and pharmaceutical industries. The structure and dynamics of sodium alginate were here investigated by measuring chemical shift anisotropy (CSA) parameters, spin-lattice relaxation time, and molecular correlation time. The principal components of the CSA tensor were determined by two-dimensional phase-adjusted spinning sideband (2DPASS) cross-polarization magic angle spinning (CP-MAS) SSNMR. The alternating M and G blocks of both equatorial and axial links are associated with greater overall flexibility. The molecular correlation time of the carboxyl carbon of both G and M blocks is faster than for the anomeric carbon and pyranose carbon. This is further experimental evidence of the coexistence of two different dynamics within the polysaccharide chains of sodium alginate, which was previously established by 1H-13C dipolar profile analysis. The relaxation time of the para-crystalline region of sodium alginate is comparable with that of chitosan, but it is much shorter than that of cellulose and chitin. The order of the molecular correlation time of sodium alginate and chitosan is also the same. Hence, it can be concluded that sodium alginate exhibits greater flexibility than cellulose and chitin. These types of investigation into the local electronic configuration and nuclear spin dynamics at various carbon nuclei sites of the biopolymer at atomic-scale resolution will help in the design of biomimetic materials.