Sodium silicate solutions, also known as waterglass, have been found to have remarkable utility in a variety of applications. The cumulative weight of evidence from 70 years of varied analysis indicates that silicate solutions consist of a wide range of species, from monomers through oligomers, up to colloids. Moreover, the structure and distribution of these species are greatly dependent upon many parameters, such as solute concentrations, silica to alkali ratio, pH, and temperature. The most interesting and characteristic property of silicate solutions is their ability to form silica gels. Overall, despite extensive research using different spectroscopic and scattering techniques, many questions related to sodium silicate\'s dynamic structure, stability, polymerization, and gelation remain difficult to answer. The multitude of simultaneous reactions which restructure the silicate species at the atomic scale in response to variation in solution and environmental parameters, makes it difficult to investigate the individual events using only experimental data. Molecular modelling provides an alternative way to study the unknown areas in the aqueous silicate and silica gel systems, generating key insights into the chemical reactions at microscopic length scales. However, sufficient sampling remains a challenge for the practical use of molecular simulation for these systems. Based on both experimental and modelling studies, this review provides a detailed discussion over the structure and speciation of sodium silicate solutions, their gelation mechanism and kinetics, and the syneresis phenomenon. The goal is not only to review the current level of understanding of sodium silicate solutions, silica gels and characterization techniques suitable for studying them, but also to identify the gaps in the literature and open up opportunities for advancing knowledge about these complex systems. We believe that the future direction of research should be toward correlating atomistic, molecular, and meso-scale level details of interactions and reactions in silicate solution and establishing a fundamental understanding of its gelation mechanism and kinetics. We believe that this knowledge could eliminate the \"trial and error\" approach in manufacturing, and improve structural control in the synthesis of important materials derived from these solutions, such as silica gels and zeolites.

The global impact of the COVID-19 pandemic caused by SARS-CoV-2 necessitates innovative strategies for the rapid development of effective treatments. Computational methodologies, such as molecular modelling, molecular dynamics simulations, and artificial intelligence, have emerged as indispensable tools in the drug discovery process. This review aimed to provide a comprehensive overview of these computational approaches and their application in the design of antiviral agents for COVID-19. Starting with an examination of ligand-based and structure-based drug discovery, the review has delved into the intricate ways through which molecular modelling can accelerate the identification of potential therapies. Additionally, the investigation extends to phytochemicals sourced from nature, which have shown promise as potential antiviral agents. Noteworthy compounds, including gallic acid, naringin, hesperidin, Tinospora cordifolia, curcumin, nimbin, azadironic acid, nimbionone, nimbionol, and nimocinol, have exhibited high affinity for COVID-19 Mpro and favourable binding energy profiles compared to current drugs. Although these compounds hold potential, their further validation through in vitro and in vivo experimentation is imperative. Throughout this exploration, the review has emphasized the pivotal role of computational biologists, bioinformaticians, and biotechnologists in driving rapid advancements in clinical research and therapeutic development. By combining state-of-the-art computational techniques with insights from structural and molecular biology, the search for potent antiviral agents has been accelerated. The collaboration between these disciplines holds immense promise in addressing the transmissibility and virulence of SARS-CoV-2.

Drug discovery, vaccine design, and protein interaction studies are rapidly moving toward the routine use of molecular dynamics simulations (MDS) and related methods. As a result of MDS, it is possible to gain insights into the dynamics and function of identified drug targets, antibody-antigen interactions, potential vaccine candidates, intrinsically disordered proteins, and essential proteins. The MDS appears to be used in all possible ways in combating diseases such as cancer, however, it has not been well documented as to how effectively it is applied to infectious diseases such as Leishmaniasis. As a result, this review aims to survey the application of MDS in combating leishmaniasis. We have systematically collected articles that illustrate the implementation of MDS in drug discovery, vaccine development, and structural studies related to Leishmaniasis. Of all the articles reviewed, we identified that only a limited number of studies focused on the development of vaccines against Leishmaniasis through MDS. Also, the PCA and FEL studies were not carried out in most of the studies. These two were globally accepted utilities to understand the conformational changes and hence it is recommended that this analysis should be taken up in similar approaches in the future.

Cancer cells require a higher amount of energy in the form of fatty acids for their uncontrolled proliferation and growth. Fatty acid synthase (FASN) plays a crucial role in the synthesis of palmitate, which is involved in most of the critical malignant pathways. Hence, by targeting FASN, tumour growth can be controlled. By designing and developing FASN inhibitors with catalytic domain specificity, safe and potential anticancer drugs can be achieved. The article draws light towards the catalytic domains of FASN, their active site residues and interaction of some of the reported natural FASN inhibitors (resveratrol, lavandulyl flavonoids, catechins, stilbene derivatives, etc). The rationality (structure-activity relationship) behind the variation in the activity of the reported natural FASN inhibitors (butyrolactones, polyphenolics, galloyl esters and thiolactomycins) has also been covered. Selective, safe and potentially active FASN inhibitors could be developed by: (i) having proper understanding of the function of all catalytic domains of FASN (ii) studying the upstream and downstream FASN regulators (iii) identifying cancer-specific FASN biomarkers (that are non-essential/absent in the normal healthy cells) (iv) exploring the complete protein structure of FASN, e-screening of the compounds prior to synthesis and study their ADME properties (v) predicting the selectivity based on their strong affinity at the catalytic site of FASN.

Type 2 Diabetes Mellitus (T2DM) is one of the highly prevalence disorder and increasing day by day worldwidely. T2DM is a metabolic disorder, which is characterized by deficiency in insulin or resistance to insulin and thus increases the glucose levels in the blood. Various approaches are there to treat diabetes but still there is no cure for this disease. DPP-4 inhibitor is a privileged target in the field of drug discovery and provides various opportunities in exploring this target for development of molecules as antidiabetic agents. DPP-4 acts by inhibiting the incretin action and thus decreases the level of blood glucose by imparting minimal side effects. Sitagliptin, vildagliptin, linagliptin etc. are the different DPP-4 based drugs approved throughout the world for the treatment of diabetes mellitus. Cyanopyrrolidines, triazolopiperazine amide, pyrrolidines are basic core nucleus present in various DPP-4 inhibitors and has potential effects. In the past few years, researchers had applied various approaches to synthesize potent DPP-4 inhibitors as antidiabetic agent without side effects like weight gain, cardiovascular risks, retinopathy etc. This review will also emphasize the recent strategies and rationale utilized by researchers for the development of DPP-4 inhibitors. This review also reveals about the various other approaches like molecular modelling, ligand based drug designing, high throughput screening etc. are used by the various research group for the development of potential DPP-4 inhibitors.

Lymphocyte-specific protein tyrosine kinase (Lck), a non-receptor Src family kinase, has a vital role in various cellular processes such as cell cycle control, cell adhesion, motility, proliferation, and differentiation. Lck is reported as a key factor regulating the functions of T-cell including the initiation of TCR signalling, T-cell development, in addition to T-cell homeostasis. Alteration in expression and activity of Lck results in numerous disorders such as cancer, asthma, diabetes, rheumatoid arthritis, atherosclerosis, and neuronal diseases. Accordingly, Lck has emerged as a novel target against different diseases. Herein, we amass the research efforts in literature and pharmaceutical patents during the last decade to develop new Lck inhibitors. Additionally, structure-activity relationship studies (SAR) and docking models of these new inhibitors within the active site of Lck were demonstrated offering deep insights into their different binding modes in a step towards the identification of more potent, selective, and safe Lck inhibitors.

After restricting the proliferation of CD4+T cells, Human Immunodeficiency Virus (HIV), infection persists at a very fast rate causing Acquired Immunodeficiency Syndrome (AIDS). This demands the vigorous need of suitable anti-HIV agents, as existing medicines do not provide a complete cure and exhibit drawbacks like toxicities, drug resistance, side-effects, etc. Even the introduction of Highly Active Antiretroviral Therapy (HAART) failed to combat HIV/AIDS completely. The major breakthrough in anti-HIV discovery was marked with the discovery of raltegravir in 2007, the first integrase (IN) inhibitor. Thereafter, the discovery of elvitegravir, a quinolone derivative emerged as the potent HIV-IN inhibitor. Though many more classes of different drugs that act as anti-HIV have been identified, some of which are under clinical trials, but the recent serious focus is still laid on quinoline and its analogues. In this review, we have covered all the quinoline-based derivatives that inhibit various targets and are potential anti-HIV agents in various phases of the drug discovery.

Prolonged antibiotic therapy for the bacterial infections has resulted in high levels of antibiotic resistance. Initially, bacteria are susceptible to the antibiotics, but can gradually develop resistance. Treating such drug-resistant bacteria remains difficult or even impossible. Hence, there is a need to develop effective drugs against bacterial pathogens. The drug discovery process is time-consuming, expensive and laborious. The traditionally available drug discovery process initiates with the identification of target as well as the most promising drug molecule, followed by the optimization of this, in-vitro, in-vivo and in pre-clinical studies to decide whether the compound has the potential to be developed as a drug molecule. Drug discovery, drug development and commercialization are complicated processes. To overcome some of these problems, there are many computational tools available for new drug discovery, which could be cost effective and less time-consuming. In-silico approaches can reduce the number of potential compounds from hundreds of thousands to the tens of thousands which could be studied for drug discovery and this results in savings of time, money and human resources. Our review is on the various computational methods employed in new drug discovery processes.