Advances In Computational Studies Research Articles

Design, synthesis, and computational analysis (molecular docking, DFT, MEP, RDG, ELF) of diazepine and oxazepine sulfonamides: biological evaluation for in vitro and in vivo anti-inflammatory, antimicrobial, and cytotoxicity predictions.

We report the synthesis and extensive characterization of Diazepane and Oxazepane derivatives, followed by their biological evaluation. These compounds were assessed for in vitro and in vivo antimicrobial, anti-inflammatory, and anticancer activities. Among the synthesized molecules, compound 5b demonstrated remarkable antibacterial activity against Staphylococcus aureus and Staphylococcus epidermidis with MIC values of 20 and 40 μg/mL, respectively. Additionally, 5b exhibited potent anti-inflammatory effects both in vitro and in vivo. Advanced computational studies, including DFT, MEP, RDG, and ELF analyses, were performed to understand the electronic distribution and molecular interactions. The bioactivity and physicochemical properties of these derivatives were further predicted using PASS and pkCSM platforms, emphasizing their potential as promising lead molecules in drug development.

Pathological insights derived from neuroimaging in amyotrophic lateral sclerosis: emerging clinical applications.

Neuroimaging has been instrumental in shaping current understanding of the pathoanatomical signature of amyotrophic lateral sclerosis (ALS) across clinically well defined patient cohorts. The potential utility of imaging as an objective disease marker, however, remains poorly defined. Increasingly advanced quantitative and computational imaging studies have highlighted emerging clinical applications for neuroimaging as a complementary clinical modality for diagnosis, monitoring, and modelling disease propagation. Multimodal neuroimaging has demonstrated novel approaches for capturing primary motor disease. Extra-motor subcortical dysfunction is increasingly recognized as key modulators of disease propagation. The neural signature of cortical and subcortical dysfunction in ALS has been well defined at the population level. Objective metrics of focal primary motor dysfunction are increasingly sensitive and translatable to the individual patient level. Integrity of extra-motor subcortical abnormalities are recognized to represent critical pathways of the ALS disease 'connectome', predicting pathological spread. Neuroimaging plays a pivotal role in capturing upper motor neuron pathology in ALS. Their potential clinical role as objective disease markers for disease classification, longitudinal monitoring, and prognosis in ALS have become increasingly well defined.

A Novel Approach for Tailoring of a Corrosion Inhibitor for Mild Steel in 1 M Hydrochloric Acid Medium: Combined Advanced Computational and Experimental Studies for Developing a Novel Quinoline Based Corrosion Inhibitor

A Novel Approach for Tailoring of a Corrosion Inhibitor for Mild Steel in 1 M Hydrochloric Acid Medium: Combined Advanced Computational and Experimental Studies for Developing a Novel Quinoline Based Corrosion Inhibitor

Revolutionizing anti-cancer drug discovery against breast cancer and lung cancer by modification of natural genistein: an advanced computational and drug design approach.

Breast and lung cancer are two of the most lethal forms of cancer, responsible for a disproportionately high number of deaths worldwide. Both doctors and cancer patients express alarm about the rising incidence of the disease globally. Although targeted treatment has achieved enormous advancements, it is not without its drawbacks. Numerous medicines and chemotherapeutic drugs have been authorized by the FDA; nevertheless, they can be quite costly and often fall short of completely curing the condition. Therefore, this investigation has been conducted to identify a potential medication against breast and lung cancer through structural modification of genistein. Genistein is the active compound in Glycyrrhiza glabra (licorice), and it exhibits solid anticancer efficiency against various cancers, including breast cancer, lung cancer, and brain cancer. Hence, the design of its analogs with the interchange of five functional groups-COOH, NH2 and OCH3, Benzene, and NH-CH2-CH2-OH-have been employed to enhance affinities compared to primary genistein. Additionally, advanced computational studies such as PASS prediction, molecular docking, ADMET, and molecular dynamics simulation were conducted. Firstly, the PASS prediction spectrum was analyzed, revealing that the designed genistein analogs exhibit improved antineoplastic activity. In the prediction data, breast and lung cancer were selected as primary targets. Subsequently, other computational investigations were gradually conducted. The mentioned compounds have shown acceptable results for in silico ADME, AMES toxicity, and hepatotoxicity estimations, which are fundamental for their oral medication. It is noteworthy that the initial binding affinity was only -8.7 kcal/mol against the breast cancer targeted protein (PDB ID: 3HB5). However, after the modification of the functional group, when calculating the binding affinities, it becomes apparent that the binding affinities increase gradually, reaching a maximum of -11.0 and -10.0 kcal/mol. Similarly, the initial binding affinity was only -8.0 kcal/mol against lung cancer (PDB ID: 2P85), but after the addition of binding affinity, it reached -9.5 kcal/mol. Finally, a molecular dynamics simulation was conducted to study the molecular models over 100 ns and examine the stability of the docked complexes. The results indicate that the selected complexes remain highly stable throughout the 100-ns molecular dynamics simulation runs, displaying strong correlations with the binding of targeted ligands within the active site of the selected protein. It is important to further investigate and proceed to clinical or wet lab experiments to determine the practical value of the proposed compounds.

Synthesis, computational and experimental pharmacological studies for (thio)ether-triazine 5-HT6R ligands with noticeable action on AChE/BChE and chalcogen-dependent intrinsic activity in search for new class of drugs against Alzheimer's disease

Alzheimer's disease is becoming a growing problem increasing at a tremendous rate. Serotonin 5-HT6 receptors appear to be a particularly attractive target from a therapeutic perspective, due to their involvement not only in cognitive processes, but also in depression and psychosis. In this work, we present the synthesis and broad biological characterization of a new series of 18 compounds with a unique 1,3,5-triazine backbone, as potent 5-HT6 receptor ligands. The main aim of this research is to compare the biological activity of the newly synthesized sulfur derivatives with their oxygen analogues and their N-demethylated O- and S-metabolites obtained for the first time. Most of the new triazines displayed high affinity (Ki < 200 nM) and selectivity towards 5-HT6R, with respect to 5-HT2AR, 5-HT7R, and D2R, in the radioligand binding assays. For selected, active compounds crystallographic studies, functional bioassays, and ADME-Tox profile in vitro were performed. The exciting novelty is that the sulfur derivatives exhibit an agonistic mode of action contrary to all other compounds obtained to date in this chemical class herein and previously reported. Advanced computational studies indicated that this intriguing functional shift might be caused by presence of chalcogen bonds formed only by the sulfur atom. In addition, the N-demethylated derivatives have emerged highly potent antioxidants and, moreover, show a significant improvement in metabolic stability compared to the parent structures. The cholinesterase study present micromolar inhibitory AChE and BChE activity for both 5-HT6 agonist 19 and potent antagonist 5. Finally, the behavioral experiments of compound 19 demonstrated its antidepressant-like properties and slight ability to improve cognitive deficits, without inducing memory impairments by itself. Described pharmacological properties of both compounds (5 and 19) allow to give a design clue for the development of multitarget compounds with 5-HT6 (both agonist and antagonist)/AChE and/or BChE mechanism in the group of 1,3,5-triazine derivatives.

Triiodothyronine positively regulates endoplasmic reticulum-associated degradation (ERAD) and promotes androgenic signaling in androgen-dependent prostate cancer cells

Thyroid hormones (THs) play crucial roles in numerous physiological processes of nearly all mammalian tissues, including differentiation and metabolism. Deterioration of TH signaling has been associated with several pathologies, including cancer. The effect of highly active triiodothyronine (T3) has been investigated in many in vivo and in vitro cancer models. However, the role of T3 on cancerous prostate tissue is controversial today. Recent studies have focused on the characterization of the supportive roles of the endoplasmic reticulum-associated degradation (ERAD) and unfolded protein response (UPR) signaling in prostate cancer (PCa) and investigating new hormonal regulation patterns, including estrogen, progesterone and 1,25(OH)2D3. Additionally, androgenic signaling controlled by androgens, which are critical in PCa progression, has been shown to be regulated by other steroid hormones. Today, the effects of T3 on ERAD and UPR are unknown, the impact on androgenic signaling is also still not fully understood in PCa. Therefore, we aimed to investigate the molecular action of T3 on the ERAD mechanism and UPR signaling in PCa cells and also extensively examined the effect of T3 on androgenic signaling. Our data indicated that T3 tightly regulated ERAD and UPR signaling in androgen-dependent PCa cells. We also found that T3 hormone stimulated androgenic signaling by upregulating AR mRNA and protein levels and enhancing its nuclear translocation. Additionally, advanced computational studies supported the ligand binding effect of T3 on AR protein. Our data suggest that targeting thyroidal signaling should be considered in therapeutic approaches to be developed for prostate malignancy in addition to other steroidal regulations.

Recent advances in computational studies on Cu-catalyzed aerobic reactions: cooperation of copper catalysts and dioxygen.

O2, one of the ideal oxidants, suffers from low solubility, low oxidizability, low selectivity and a triplet ground state when applied in organic synthesis. Biomimetic copper catalysis has been demonstrated to be a powerful method for activating and transforming O2 to conduct aerobic reactions for a long time. On the other hand, the structures of Cu-O2 complexes are complex with diverse downstream reactions, whereas active copper intermediates were rarely identified by experimental methods, making the mechanisms of many Cu-catalyzed aerobic reactions far from clear. In this context, computational studies emerged as an effective alternative to mechanistic studies on Cu-catalyzed aerobic reactions. This review introduces the relevant computational studies since 2012, focusing on showing the cooperation of copper catalysts and O2 in dehydrogenation, oxygenation and coupling reactions.

AROMATICITY OF AZA AROMATIC MOLECULES: PREDICTION FROM HÜCKEL THEORY WITH MODIFIED PARAMETERS

Hückel theory is a simple and powerful method for predicting the molecular orbital and the energy of conjugated molecules. However, the presence of nitrogen atoms in aza aromatic molecules alters the Coulomb and resonance integrals owing to the difference in electronegativity between nitrogen and carbon atoms. In this study, we focus on acridine and phenazine. Further correction is implemented based on the ring current model, thus revealing the change in resonance integral for the carbon–carbon bond along the bridge of the molecule. The Hamiltonian of the π–electron system in the Hückel method is solved using the HuLiS software. Various geometry-based aromaticity indices are used to obtain the aromaticity indices of the two non-equivalent rings. For further evaluation, the results for bond lengths are used to calculate the associated bond energy. Considering the carbon–hydrogen (CH) bonds, the total molecular energy is compared with the experimental heats of formation for a number of benzenoid hydrocarbons and aza aromatics, in addition to the two studied molecules. Finally, the correlation between the nitrogen atom on the aromaticity index and the ring energy content is evaluated to determine to which extent the Hückel model agrees with previous experimental and advanced computational studies.

The Interplay Between Experimental Spectroscopy, Theoretical, and Computational Quantum Chemistry

Advances in technology led to development of sophisticated experimental techniques for studying new chemical systems and processes on the molecular levels. Such experimental observations required advanced computational and theorical studies to enable observations and analysis of the data. This led to evolution of new theoretical models and computational methods that have been proven valuable in aiding experimental detection and interpretation of results. Collaborative research between theorists and experimentalists became essential in the various areas chemistry, such as identification and determination of properties of new important hydrogen-bonded and chemically-bonded chemical species. These molecular systems are of importance in the atmospheric chemistry, development of new materials from large clusters, drug design, reactions and interactions in biological systems. This mini review provides examples of the author’s theoretical work for two different types of new chemical systems, in collaboration with experimental spectroscopists. These selected studies will be used to emphasis importance of the interplay between theory, computational chemistry, and high-resolution molecular spectroscopy in gas phase.

Recent advances in computational studies on voltage‐gated sodium channels: Drug design and mechanism studies

AbstractVoltage‐gated sodium channels (VGSCs/Navs), which control the flow of Na+ and affect the generation of action potentials (APs), have been regarded as essential targets for many diseases. The biological and pharmacological functions of VGSCs have been extensively studied and many efforts have been made to discover and design ligands of VGSCs as potential therapies. Here, we summarize the recent and representative studies of VGSCs from the perspective of computer‐aided drug design (CADD) and molecular modeling, including the structural biology of VGSCs, virtual screening and drug design toward VGSCs based on CADD, and functional studies using molecular modeling technologies. Furthermore, we conclude the achievements that have been made in the field of VGSCs and discuss the shortcomings found in previous studies. We hope that this review can provide some inspiration and reference for future investigations of VGSCs and drug design.This article is categorized under: Structure and Mechanism &gt; Computational Biochemistry and Biophysics

How do bones grow? A mathematical description of the mechanobiological behavior of the epiphyseal plate.

Growth modulation is an emerging method for the treatment of skeletal deformities originating in the long bones or the vertebral bodies. It requires the controlled application of mechanical loads to the affected bone, causing an alteration of the growth and ossification process occurring in a cartilaginous region called epiphyseal growth plate or physis. In order to avoid the possibility of under- or over-correction, quantification of the applied forces is necessary. Pursuing this goal, here we propose a phenomenological model of mechanobiological effects on the epiphyseal growth plate, based on the observed similarity between the mechanobiologically induced growth and viscoelastic material behavior. The model incorporates mechanical loading effects on growth direction, growth rate and ossification speed; it also allows to evaluate the occurrence of transient effects. Model consistency was tested against a rather large set of experiments existing in the literature. A generic simplified geometrical model of bones was established for this. Analytical solutions for growth and ossification evolution were obtained for different loading conditions, allowing to test the ability of the model to describe bone growth under various kinds of mechanical loading conditions. Model-predicted changes regarding epiphyseal growth plate thickness as well as longitudinal growth speed are consistent with experiments in which static tension or compression were applied to long bones. Results suggest that when the mechanical load is sinusoidally variable, conflicting data existing in the literature could be explained by a previously unconsidered effect of the the applied load initial phase. The model can accurately fit data regarding torsional loads effects on growth. Mechanobiological data for humans is very scarce. For this reason, when possible, the model parameters values were estimated, for the proposed generic geometry, after growth measurements in animal models available in the literature. Although it is not possible to assert their validity for humans, the proposed model along with the obtained parameters values give a rational foundation to be used in more advanced computational studies.

Emerging chemistries and molecular designs for flow batteries.

Redox flow batteries are a critical technology for large-scale energy storage, offering the promising characteristics of high scalability, design flexibility and decoupled energy and power. In recent years, they have attracted extensive research interest, with significant advances in relevant materials chemistry, performance metrics and characterization. The emerging concepts of hybrid battery design, redox-targeting strategy, photoelectrode integration and organic redox-active materials present new chemistries for cost-effective and sustainable energy storage systems. This Review summarizes the recent development of next-generation redox flow batteries, providing a critical overview of the emerging redox chemistries of active materials from inorganics to organics. We discuss electrochemical characterizations and critical performance assessment considering the intrinsic properties of the active materials and the mechanisms that lead to degradation of energy storage capacity. In particular, we highlight the importance of advanced spectroscopic analysis and computational studies in enabling understanding of relevant mechanisms. We also outline the technical requirements for rational design of innovative materials and electrolytes to stimulate more exciting research and present the prospect of this field from aspects of both fundamental science and practical applications.

Improved Quantification of Cell Density in the Arterial Wall-A Novel Nucleus Splitting Approach Applied to 3D Two-Photon Laser-Scanning Microscopy.

Accurate information on vascular smooth muscle cell (VSMC) content, orientation, and distribution in blood vessels is indispensable to increase understanding of arterial remodeling and to improve modeling of vascular biomechanics. We have previously proposed an analysis method to automatically characterize VSMC orientation and transmural distribution in murine carotid arteries under well-controlled biomechanical conditions. However, coincident nuclei, erroneously detected as one large nucleus, were excluded from the analysis, hampering accurate VSMC content characterization and distorting transmural distributions. In the present study, therefore, we aim to (1) improve the previous method by adding a “nucleus splitting” procedure to split coinciding nuclei, (2) evaluate the accuracy of this novel method, and (3) test this method in a mouse model of VSMC apoptosis. After euthanasia, carotid arteries from SM22α-hDTR Apoe–/– and control Apoe–/– mice were bluntly dissected, excised, mounted in a biaxial biomechanical tester and brought to in vivo axial stretch and a pressure of 100 mmHg. Nuclei and elastin fibers were then stained using Syto-41 and Eosin-Y, respectively, and imaged using 3D two-photon laser scanning microscopy. Nuclei were segmented from images and coincident nuclei were split. The nucleus splitting procedure determines the likelihood that voxel pairs within coincident nuclei belong to the same nucleus and utilizes these likelihoods to identify individual nuclei using spectral clustering. Manual nucleus counts were used as a reference to assess the performance of our splitting procedure. Before and after splitting, automatic nucleus counts differed −26.6 ± 9.90% (p < 0.001) and −1.44 ± 7.05% (p = 0.467) from the manual reference, respectively. Whereas the slope of the relative difference between the manual and automated counts as a function of the manual count was significantly negative before splitting (p = 0.008), this slope became insignificant after splitting (p = 0.653). Smooth muscle apoptosis led to a 33.7% decrease in VSMC density (p = 0.008). Nucleus splitting improves the accuracy of automated cell content quantification in murine carotid arteries and overcomes the progressively worsening problem of coincident nuclei with increasing cell content in vessels. The presented image analysis framework provides a robust tool to quantify cell content, orientation, shape, and distribution in vessels to inform experimental and advanced computational studies on vascular structure and function.

Molecular Modeling Strategies of Cancer Multidrug Resistance.

Cancer remains a leading cause of morbidity and mortality worldwide. Hence, the increase in cancer cases observed in the elderly population, as well as in children and adolescents, makes human malignancies a prime target for anticancer drug development. Although highly effective chemotherapeutic agents are continuously developed and approved for clinical treatment, the major impediment towards curative cancer therapy remains multidrug resistance (MDR). In recent years, intensive studies have been carried out on the identification of new therapeutic molecules to reverse MDR efflux transporters of the ATP-binding cassette (ABC) superfamily. Although a great deal of progress has been made in the development of specific inhibitors for certain MDR efflux pumps in experimental studies, advanced computational studies can accelerate this drug development process. In the literature, there are many experimental studies on the impact of natural products and synthetic small molecules on the reversal of cancer MDR. Molecular modeling methods provide an opportunity to explain the activity of these molecules on the ABC-transporter family with non-covalent interactions as well as it is possible to carry out studies for the discovery of new anticancer drugs specific to MDR with these methods. The coordinate file of the 3-dimensional (3D) structure of the target protein is indispensable for molecular modeling studies. In some cases where a 3D structure cannot be obtained by experimental methods, the homology modeling method can be applied to obtain the file containing the target protein's information including atomic coordinates, secondary structure assignments, and atomic connectivity. Homology modeling studies are of great importance for efflux transporter proteins that still lack 3D structures due to crystallization problems with multiple hydrophobic transmembrane domains. Quantum mechanics, molecular docking and molecular dynamics simulation applications are the most frequently used molecular modeling methods in the literature to investigate non-covalent interactions between the drug-ABC transporter superfamily. The quantitative structure-activity relationship (QSAR) model provides a relationship between the chemical properties of a compound and its biological activity. Determining the pharmacophore region for a new drug molecule by superpositioning a series of molecules according to their physicochemical properties using QSAR models is another method in which molecular modeling is used in computational drug development studies with ABC transporter proteins. There are also in silico absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) studies conducted to make a prediction about the pharmacokinetic properties, and drug-likeness of new molecules. Drug repurposing studies, which have become a trending topic in recent years, involve identifying possible new targets for an already approved drug molecule. There are few studies in the literature in which drug repurposing performed by molecular modelling methods has been applied on ABC transporter proteins. The aim of the current paper is to create a complete review of drug development studies including aforementioned molecular modeling methods carried out between the years 2019-2021. Furthermore, an intensive investigation is also conducted on licensed applications and free web servers used in in silico studies. The current review is an up-to-date guide for researchers who plan to conduct computational studies with MDR transporter proteins.

Ionic liquid incorporation in zeolitic imidazolate framework-3 for improved CO2 separation: A computational approach

Selective adsorption of gases from various mixtures of industrial importance has become a major concern. Improving the selectivity of the existing material by chemical/physical modification can solve this problem to an extent. In this regard, we incorporated ILs into the pores of well-known porous material, zeolitic imidazolate framework (ZIF). ZIF-3 has shown good selectivity for CO2 but their modification with ionic liquid (IL) has not yet explored. We studied 1-butyl-3-methylimidazolium ([BMIM]+) cation with seven different anions inside the confinement of ZIF-3 and their effect on the separation of CO2. Different orientations are checked and the stable one is selected for advanced computational studies. Pristine ZIF-3 and IL impregnated ZIF-3 shows good adsorption potential for CO2. The incorporation of ILs in ZIF-3 significantly enhances the CO2 capture from CO2/N2 and CO2/CH4 gaseous mixture. Whereas it is interesting that the adsorption of methane from CH4/N2 highly depends on the nature of IL (i.e. anion) inside the ZIF-3. Adsorption energies and heat of adsorption gives the strength of interaction between ILs, ZIF-3 and guest gaseous molecules. The ILs@ZIF-3 composites can perform better than well-known IL@ZIF-8 composite at higher pressure. The investigation of IL incorporation to various ZIFs can offer better CO2 selective material than the existing ones in the near future. Our combined density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations are used to get more insights on the interfacial interactions between the ILs-ZIF structures and how these molecular level interactions can be helpful in the gas sensor applications and industrial flue gas separations.

Calcium fluoride as high-k dielectric for 2D electronics

Calcium fluoride is a dielectric material with a wide bandgap (∼12.1 eV) and a relatively high dielectric constant (∼6.8) that forms a van der Waals interface with two-dimensional (2D) materials, meaning that it contains a very low amount of defects. Thin calcium fluoride films can be synthesized using multiple techniques that are scalable to the wafer level, including molecular beam epitaxy, atomic layer deposition, and chemical vapor deposition. However, the consolidation of calcium fluoride as dielectric for 2D electronics requires overcoming some fundamental challenges related to material quality and integration, as well as carrying out advanced characterization and computational studies to evaluate its real potential. Here, we review the status of calcium fluoride dielectric films in terms of material synthesis, fundamental electrical properties, and future applications; we also discuss the most important challenges of calcium fluoride integration in 2D materials–based, solid-state nano/micro-electronic devices, and propose several potential routes to overcome them. Our manuscript may serve as a useful guide for other scientists working on 2D electronics in general, and provides a clear pathway for calcium fluoride research in the future.

Identification of Single-Atom Ni Site Active toward Electrochemical CO2 Conversion to CO.

Electrocatalytic conversion of CO2 into value-added products offers a new paradigm for a sustainable carbon economy. For active CO2 electrolysis, the single-atom Ni catalyst has been proposed as promising from experiments, but an idealized Ni-N4 site shows an unfavorable energetics from theory, leading to many debates on the chemical nature responsible for high activity. To resolve this conundrum, here we investigated CO2 electrolysis of Ni sites with well-defined coordination, tetraphenylporphyrin (N4-TPP) and 21-oxatetraphenylporphyrin (N3O-TPP). Advanced spectroscopic and computational studies revealed that the broken ligand-field symmetry is the key for active CO2 electrolysis, which subordinates an increase in the Ni redox potential yielding NiI. Along with their importance in activity, ligand-field symmetry and strength are directly related to the stability of the Ni center. This suggests the next quest for an activity-stability map in the domain of ligand-field strength, toward a rational ligand-field engineering of single-atom Ni catalysts for efficient CO2 electrolysis.

Probing the Solid Phase of Noble Metal Copper at Terapascal Conditions.

Ramp compression along a low-temperature adiabat offers a unique avenue to explore the physical properties of materials at the highest densities of their solid form, a region inaccessible by single shock compression. Using the National Ignition Facility and OMEGA laser facilities, copper samples were ramp compressed to peak pressures of 2.30TPa and densities of nearly 30 g/cc, providing fundamental information regarding the compressibility and phase of copper at pressures more than 5 times greater than previously explored. Through x-ray diffraction measurements, we find that the ambient face-centered-cubic structure is preserved up to 1.15TPa. The ramp compression equation-of-state measurements shows that there are no discontinuities in sound velocities up to 2.30TPa, suggesting this phase is likely stable up to the peak pressures measured, as predicted by first-principal calculations. The high precision of these quasiabsolute measurements enables us to provide essential benchmarks for advanced computational studies on the behavior of dense monoatomic materials under extreme conditions that constitute a stringent test for solid-state quantum theory. We find that both density-functional theory and the stabilized jellium model, which assumes that the ionic structure can be replaced by an ionic charge distribution by constant positive-charge background, reproduces our data well. Further, our data could serve to establish new international secondary scales of pressure in the terapascal range that is becoming experimentally accessible with advanced static and dynamic compression techniques.

Recent advances in computational studies of GPCR-G protein interactions.

Protein-protein interactions are key in cellular signaling. G protein-coupled receptors (GPCRs), the largest superfamily of human membrane proteins, are able to transduce extracellular signals (e.g., hormones and neurotransmitters) to intracellular proteins, in particular the G proteins. Since GPCRs serve as primary targets of ~1/3 of currently marketed drugs, it is important to understand mechanisms of GPCR signaling in order to design selective and potent drug molecules. This chapter focuses on recent advances in computational studies of the GPCR-G protein interactions using bioinformatics, protein-protein docking and molecular dynamics simulation approaches.

Advances in Computational Studies of Potential Drug Targets in Mycobacterium tuberculosis.

Tuberculosis continues to remain as one of the leading causes of death worldwide, in spite of significant progress being made in the last twenty years through increased compliance to treatment. The current review gives an overview of the recent efforts made in the endeavor to identify novel inhibitors and promising drug targets for Mycobacterium tuberculosis with structure and ligand-based approaches along with bioinformatics studies following complete sequencing of its genome. A large number of these studies target biomolecules in metabolic pathways that are vital for the survival of the microorganism. A discussion on efforts to study metalloproteins as relatively underexplored targets in the context of their druggability is also presented.