Unveiling critical structural features for effective HDAC8 inhibition: a comprehensive study using quantitative read-across structure-activity relationship (q-RASAR) and pharmacophore modeling.

Histone deacetylases constitute a group of enzymes that participate in several biological processes. Notably, inhibiting HDAC8 has become a therapeutic strategy for various diseases. The current inhibitors for HDAC8 lack selectivity and target multiple HDACs. Consequently, there is a growing recognition of the need for selective HDAC8 inhibitors to enhance the effectiveness of therapeutic interventions. In our current study, we have utilized a multi-faceted approach, including Quantitative Structure-Activity Relationship (QSAR) combined with Quantitative Read-Across Structure-Activity Relationship (q-RASAR) modeling, pharmacophore mapping, molecular docking, and molecular dynamics (MD) simulations. The developed q-RASAR model has a high statistical significance and predictive ability (Q2F1:0.778, Q2F2:0.775). The contributions of important descriptors are discussed in detail to gain insight into the crucial structural features in HDAC8 inhibition. The best pharmacophore hypothesis exhibits a high regression coefficient (0.969) and a low root mean square deviation (0.944), highlighting the importance of correctly orienting hydrogen bond acceptor (HBA), ring aromatic (RA), and zinc-binding group (ZBG) features in designing potent HDAC8 inhibitors. To confirm the results of q-RASAR and pharmacophore mapping, molecular docking analysis of the five potent compounds (44, 54, 82, 102, and 118) was performed to gain further insights into these structural features crucial for interaction with the HDAC8 enzyme. Lastly, MD simulation studies of the most active compound (54, mapped correctly with the pharmacophore hypothesis) and the least active compound (34, mapped poorly with the pharmacophore hypothesis) were carried out to validate the observations of the studies above. This study not only refines our understanding of essential structural features for HDAC8 inhibition but also provides a robust framework for the rational design of novel selective HDAC8 inhibitors which may offer insights to medicinal chemists and researchers engaged in the development of HDAC8-targeted therapeutics.

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.

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.

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.

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.

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.

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.

Protease targeted COVID-19 drug discovery and its challenges: Insight into viral main protease (Mpro) and papain-like protease (PLpro) inhibitors.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) brutally perils physical and mental health worldwide. Unavailability of effective anti-viral drug rendering global threat of COVID-19 caused by SARS-CoV-2. In this scenario, viral protease enzymes are crucial targets for drug discovery. This extensive study meticulously focused on two viral proteases such as main protease (Mpro) and papain-like protease (PLpro), those are essential for viral replication. This review provides a detail overview of the targets (Mpro and PLpro) from a structural and medicinal chemistry point of view, together with recently reported protease inhibitors. An insight into the challenges in the development of effective as well as drug like protease inhibitors is discussed. Peptidomimetic and/or covalent coronavirus protease inhibitors possessed potent and selective active site inhibition but compromised in pharmacokinetic parameters to be a drug/drug like molecule. Lead optimization of non-peptidomimetic and/or low molecular weight compounds may be a better option for oral delivery. A masterly combination of adequate pharmacokinetic properties with coronavirus protease activity as well as selectivity will provide potential drug candidates in future. This study is a part of our endeavors which surely dictates medicinal chemistry efforts to discover effective anti-viral agent for this devastating disease.

First structure-activity relationship analysis of SARS-CoV-2 virus main protease (Mpro) inhibitors: an endeavor on COVID-19 drug discovery.

Main protease (Mpro) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) intervenes in the replication and transcription processes of the virus. Hence, it is a lucrative target for anti-viral drug development. In this study, molecular modeling analyses were performed on the structure activity data of recently reported diverse SARS-CoV-2 Mpro inhibitors to understand the structural requirements for higher inhibitory activity. The classification-based quantitative structure-activity relationship (QSAR) models were generated between SARS-CoV-2 Mpro inhibitory activities and different descriptors. Identification of structural fingerprints to increase or decrease in the inhibitory activity was mapped for possible inclusion/exclusion of these fingerprints in the lead optimization process. Challenges in ADME properties of protease inhibitors were also discussed to overcome the problems of oral bioavailability. Further, depending on the modeling results, we have proposed novel as well as potent SARS-CoV-2 Mpro inhibitors.

Unmasking of crucial structural fragments for coronavirus protease inhibitors and its implications in COVID-19 drug discovery.

Fragment based drug discovery (FBDD) by the aid of different modelling techniques have been emerged as a key drug discovery tool in the area of pharmaceutical science and technology. The merits of employing these methods, in place of other conventional molecular modelling techniques, endorsed clear detection of the possible structural fragments present in diverse set of investigated compounds and can create alternate possibilities of lead optimization in drug discovery. In this work, two fragment identification tools namely SARpy and Laplacian-corrected Bayesian analysis were used for previous SARS-CoV PLpro and 3CLpro inhibitors. A robust and predictive SARpy based fragments identification was performed which have been validated further by Laplacian-corrected Bayesian model. These comprehensive approaches have advantages since fragments are straight forward to interpret. Moreover, distinguishing the key molecular features (with respect to ECFP_6 fingerprint) revealed good or bad influences for the SARS-CoV protease inhibitory activities. Furthermore, the identified fragments could be implemented in the medicinal chemistry endeavors of COVID-19 drug discovery.

Chemical-informatics approach to COVID-19 drug discovery: Exploration of important fragments and data mining based prediction of some hits from natural origins as main protease (Mpro) inhibitors.

As the world struggles against current global pandemic of novel coronavirus disease (COVID-19), it is challenging to trigger drug discovery efforts to search broad-spectrum antiviral agents. Thus, there is a need of strong and sustainable global collaborative works especially in terms of new and existing data analysis and sharing which will join the dots of knowledge gap. Our present chemical-informatics based data analysis approach is an attempt of application of previous activity data of SARS-CoV main protease (Mpro) inhibitors to accelerate the search of present SARS-CoV-2 Mpro inhibitors. The study design was composed of three major aspects: (1) classification QSAR based data mining of diverse SARS-CoV Mpro inhibitors, (2) identification of favourable and/or unfavourable molecular features/fingerprints/substructures regulating the Mpro inhibitory properties, (3) data mining based prediction to validate recently reported virtual hits from natural origin against SARS-CoV-2 Mpro enzyme. Our Structural and physico-chemical interpretation (SPCI) analysis suggested that heterocyclic nucleus like diazole, furan and pyridine have clear positive contribution while, thiophen, thiazole and pyrimidine may exhibit negative contribution to the SARS-CoV Mpro inhibition. Several Monte Carlo optimization based QSAR models were developed and the best model was used for screening of some natural product hits from recent publications. The resulted active molecules were analysed further from the aspects of fragment analysis. This approach set a stage for fragment exploration and QSAR based screening of active molecules against putative SARS-CoV-2 Mpro enzyme. We believe the future in vitro and in vivo studies would provide more perspectives for anti-SARS-CoV-2 agents.

Structure-activity relationship of human carbonic anhydrase-II inhibitors: Detailed insight for future development as anti-glaucoma agents.

Human carbonic anhydrase-II (hCA-II) is the most dominant physiologic isoform amongst the sixteen reported hCA isoforms. Because of its high availability in the different anatomical, and cellular sites of the eye like retina and lens, it plays a more prominent role in the regulation of intraocular pressure than the other twelve catalytically active hCA isoforms. This isoform is also located in the brain, kidney, gastric mucosa, osteoclasts, RBCs, skeletal muscle, testes, pancreas, lungs, etc. Earlier, hCA-II inhibitors were designed based on the sulfonamides e.g. acetazolamide, dichlorphenamide, methazolamide, ethoxzolamide, etc. and they were used systemically in antiglaucoma therapy. Many successful attempts have been made by the researchers in order to design more potent and effective inhibitors by incorporating various moieties in sulphonamides. Some novel scaffolds like chalcones, thiophenes, organotellurium compounds, dithiocarbamate, selenide, and 2-benzylpyrazine, etc. were also designed as hCA-II inhibitors and their inhibitory efficacy was proved in the nanomolar range. In order to obtain relevant information from the insights of their structure-activity relationship, the reported hCA-II inhibitors from the year 1989 to 2019 were critically analysed. It gave a complete insight into the relationship between their structure-activity and hCA-II inhibition. The broad spectrum of our investigation may help researchers to summarize all the crucial structural information required for the development of more potent hCA-II inhibitors for glaucoma.

Identification of structural fingerprints for in vivo toxicity by using Monte Carlo based QSTR modeling of nitroaromatics.

Monte Carlo based method by using either SMILES based or combination of SMILES and Graph-based descriptors is an important strategy to build the QSAR/QSTR model for prediction of different biological endpoints. In this study, Monte Carlo based QSTR approach was applied to the dataset of 90 nitroaromatic compounds related to their in vivo toxicity, represented by 50% lethal dose concentration for rats (LD50). Both classification and regression-based QSTR models were developed to get an idea about different fingerprints for promoters and hinderers of nitroaromatics toxicity. The best classification model was obtained by using SMILES and graph-based (GAO) descriptor with 1ECK connectivity (sensitivity = 0.7143, specificity = 1.0000, accuracy = 0.8889, and MCC = 0.7774). The best regression model calculated by using SMILES and hydrogen-suppressed graph descriptors with 0ECk connectivity (R2 = 0.7386, Q2 = 0.6315, S = 0.467, and MAE = 0.340). Finally, a consensus QSTR model was generated to predict efficiently the toxicity of new compounds. The study highlighted that the comparative QSTR models by using the Monte Carlo method can also be generated and will be a useful tool for structural fingerprint analysis in case of nitroaromatics for preliminary evaluation of its toxicity to mammals.

An integrated QSAR modeling approach to explore the structure-property and selectivity relationships of N-benzoyl-L-biphenylalanines as integrin antagonists.

Integrins [Formula: see text] and [Formula: see text] are important targets to treat different inflammatory diseases, such as multiple sclerosis, inflammatory bowel diseases, rheumatoid arthritis, atherosclerosis, and asthma. Despite being valuable targets, only a few work has been reported to date regarding molecular modeling studies on these integrins. Not only that, none of these reports addressed the selectivity issue between integrins [Formula: see text] and [Formula: see text]. Therefore, a major challenge regarding the design and discovery of selective integrin antagonists remains. In this study, a series of 142 N-benzoyl-L-biphenylalanines having both integrin [Formula: see text] and [Formula: see text] inhibitory activities were considered for a variety of QSAR approaches including regression and classification-based 2D-QSARs, Hologram QSARs, 3D-QSAR CoMFA and CoMSIA studies to identify the structural requirements of these integrin antagonists. All these QSAR models were statistically validated and subsequently correlated with each other to get a detailed understanding of the activity and selectivity profiles of these molecules.

Secondary structure and membrane topology of dengue virus NS4B N-terminal 125 amino acids.

The transmembrane NS4B protein of dengue virus (DENV) is a validated antiviral target that plays important roles in viral replication and invasion of innate immune response. The first 125 amino acids of DENV NS4B are sufficient for inhibition of alpha/beta interferon signaling. Resistance mutations to NS4B inhibitors are all mapped to the first 125 amino acids. In this study, we expressed and purified a protein representing the first 125 amino acids of NS4B (NS4B(1-125)). This recombinant NS4B(1-125) protein was reconstituted into detergent micelles. Solution NMR spectroscopy demonstrated that there are five helices (α1 to α5) present in NS4B(1-125). Dynamic studies, together with a paramagnetic relaxation enhancement experiment demonstrated that four helices, α2, α3, α4, and α5 are embedded in the detergent micelles. Comparison of wild type and V63I mutant (a mutation that confers resistance to NS4B inhibitor) NS4B(1-125) proteins demonstrated that V63I mutation did not cause significant conformational changes, however, V63 may have a molecular interaction with residues in the α5 transmembrane domain under certain conditions. The structural and dynamic information obtained in study is helpful to understand the structure and function of NS4B.

First molecular modeling report on novel arylpyrimidine kynurenine monooxygenase inhibitors through multi-QSAR analysis against Huntington's disease: A proposal to chemists!

Huntington's disease (HD) is caused by mutation of huntingtin protein (mHtt) leading to neuronal cell death. The mHtt induced toxicity can be rescued by inhibiting the kynurenine monooxygenase (KMO) enzyme. Therefore, KMO is a promising drug target to address the neurodegenerative disorders such as Huntington's diseases. Fiftysix arylpyrimidine KMO inhibitors are structurally explored through regression and classification based multi-QSAR modeling, pharmacophore mapping and molecular docking approaches. Moreover, ten new compounds are proposed and validated through the modeling that may be effective in accelerating Huntington's disease drug discovery efforts.

Structural analysis of the S4-S5 linker of the human KCNQ1 potassium channel.

KCNQ1 plays important roles in the cardiac action potential and consists of an N-terminal domain, a voltage-sensor domain, a pore domain and a C-terminal domain. KCNQ1 is a voltage-gated potassium channel and its channel activity is regulated by membrane potentials. The linker between transmembrane helices 4 and 5 (S4-S5 linker) is important for transferring the conformational changes from the voltage-sensor domain to the pore domain. In this study, the structure of the S4-S5 linker of KCNQ1 was investigated by solution NMR, circular dichroism and fluorescence spectroscopic studies. The S4-S5 linker adopted a helical structure in detergent micelles. The W248 may interact with the cell membrane.

NMR analysis of a novel enzymatically active unlinked dengue NS2B-NS3 protease complex.

The dengue virus (DENV) is a mosquito-borne pathogen responsible for an estimated 100 million human infections annually. The viral genome encodes a two-component trypsin-like protease that contains the cofactor region from the nonstructural protein NS2B and the protease domain from NS3 (NS3pro). The NS2B-NS3pro complex plays a crucial role in viral maturation and has been identified as a potential drug target. Using a DENV protease construct containing NS2B covalently linked to NS3pro via a Gly4-Ser-Gly4 linker ("linked protease"), previous x-ray crystal structures show that the C-terminal fragment of NS2B is remote from NS3pro and exists in an open state in the absence of an inhibitor; however, in the presence of an inhibitor, NS2B complexes with NS3pro to form a closed state. This linked enzyme produced NMR spectra with severe signal overlap and line broadening. To obtain a protease construct with a resolved NMR spectrum, we expressed and purified an unlinked protease complex containing a 50-residue segment of the NS2B cofactor region and NS3pro without the glycine linker using a coexpression system. This unlinked protease complex was catalytically active at neutral pH in the absence of glycerol and produced dispersed cross-peaks in a (1)H-(15)N heteronuclear single quantum correlation spectrum that enabled us to conduct backbone assignments using conventional techniques. In addition, titration with an active-site peptide aldehyde inhibitor and paramagnetic relaxation enhancement studies demonstrated that the unlinked DENV protease exists predominantly in a closed conformation in solution. This protease complex can serve as a useful tool for drug discovery against DENV.

Membrane topology and function of dengue virus NS2A protein.

Flavivirus nonstructural protein 2A (NS2A) is a component of the viral replication complex that functions in virion assembly and antagonizes the host immune response. Although flavivirus NS2A is known to associate with the endoplasmic reticulum (ER) membrane, the detailed topology of this protein has not been determined. Here we report the first topology model of flavivirus NS2A on the ER membrane. Using dengue virus (DENV) NS2A as a model, we show that (i) the N-terminal 68 amino acids are located in the ER lumen, with one segment (amino acids 30 to 52) that interacts with ER membrane without traversing the lipid bilayer; (ii) amino acids 69 to 209 form five transmembrane segments, each of which integrally spans the ER membrane; and (iii) the C-terminal tail (amino acids 210 to 218) is located in the cytosol. Nuclear magnetic resonance (NMR) structural analysis showed that the first membrane-spanning segment (amino acids 69 to 93) consists of two helices separated by a "helix breaker." The helix breaker is formed by amino acid P85 and one positively charged residue, R84. Functional analysis using replicon and genome-length RNAs of DENV-2 indicates that P85 is not important for viral replication. However, when R84 was replaced with E, the mutation attenuated both viral RNA synthesis and virus production. Remarkably, an R84A mutation did not affect viral RNA synthesis but blocked intracellular formation of infectious virions. Collectively, the mutagenesis results demonstrate that NS2A functions in both DENV RNA synthesis and virion assembly/maturation. The topology model of DENV NS2A provides a good starting point for studying how flavivirus NS2A modulates viral replication and evasion of host immune response.

Structural insight into the transmembrane segments 3 and 4 of the hERG potassium channel.

The hERG (human ether-a-go-go related gene) potassium channel is a voltage-gated potassium channel containing an N-terminal domain, a voltage-sensor domain, a pore domain and a C-terminal domain. The transmembrane segment 4 (S4) is important for sensing changes of membrane potentials through positively charge residues. A construct containing partial S2-S3 linker, S3, S4 and the S4-S5 linker of the hERG channel was purified into detergent micelles. This construct exhibits good quality NMR spectrum when it was purified in lyso-myristoyl phosphatidylglycerol (LMPG) micelles. Structural study showed that S3 contains two short helices with a negatively charged surface. The S4 and S4-S5 linker adopt helical structures. The six positively charged residues in S4 localize at different sides, suggesting that they may have different functions in channel gating. Relaxation studies indicated that S3 is more flexible than S4. The boundaries of S3-S4 and S4-S4-S5 linker were identified. Our results provided structural information of the S3 and S4, which will be helpful to understand their roles in channel gating.