The Preventive and Therapeutic Potential of the Flavonoids in Liver Cirrhosis: Current and Future Perspectives.

Non-alcoholic fatty liver disease (NAFLD) may vary from moderately mild non-alcohol fatty liver (NAFL) towards the malignant variant known as non-alcoholic steatohepatitis (NASH), which is marked by fatty liver inflammation and may progress to liver cirrhosis (LC), liver cancer, fibrosis, or liver failure. Flavonoids can protect the liver from toxins through their anti-inflammatory, antioxidant, anti-cancer, and antifibrogenic pharmacological activities. Furthermore, flavonoids protect against LC by regulation of hepatic stellate cells (HSCs) trans-differentiation, inhibiting growth factors like TGF-ß and platelets-derived growth factor (PDGF), vascular epithelial growth factor (VEGF), viral infections like hepatitis-B, C and D viruses (HBV, HCV & HDV), autoimmune-induced, alcohol-induced, metabolic disorder-induced, causing by apoptosis, and regulating MAPK pathways. These flavonoids may be explored in the future as a therapeutic solution for hepatic diseases.

Differential Cationization of Fatty Acids with Monovalent Cations Studied by ESI-MS/MS and Computational Approach.

RATIONALE: The intercellular and intracellular transport of charged species (Na+ /K+ ) entail interaction of the ions with neutral organic molecules and formation of adduct ions. The rate of transport of the ions across the cell membrane(s) may depend on the stability of the adduct ions, which in turn rely on structural aspects of the organic molecules that interact with the ions. METHODS: Positive ion ESI mass spectra were recorded for the solutions containing fatty acids (FAs) and monovalent cations (X=Li+ , Na+ , K+ , Rb+ and Cs+ ). Product ion spectra of the [FA+X]+ ions were recorded at different collision energies. Theoretical studies were exploited under both gas phase and solvent phase to investigate the structural effects of the fatty acids during cationization. Stability of [FA+X]+ adduct ions were further estimated by means of AIM topological analyses and interaction energy (IE) values. RESULTS: Positive ion ESI-MS analyses of the solution of FAs and X+ ions showed preferential binding of the K+ ions to FAs. The K+ ion binding increased with the increase in number of double bonds of FAs, while decreased with increase in the number of carbons of FAs. Dissociation curves of [FA+X]+ ions indicated the relative stability order of the [FA+X]+ ions and it was in line with the observed trends in ESI-MS. The solvent phase computational studies divulged the mode of binding and the binding efficiencies of different FAs with monovalent cations. CONCLUSIONS: Among the studied monovalent cations, the cationization of FAs follow the order K+ >>Na+ >Li+ >Rb+ >Cs+ . The docosahexaenoic acid showed high efficiency in binding with K+ ion. The K+ ion binding efficiency of FAs depends on the number of double bonds in unsaturated FAs and the carbon chain length in saturated FAs. The cationization trends of FAs obtained from the ESI-MS, ESI-MS/MS analyses were in good agreement with solvent phase computational studies.

Molecular property diagnostic suite for diabetes mellitus (MPDSDM): An integrated web portal for drug discovery and drug repurposing.

Molecular Property Diagnostic Suite - Diabetes Mellitus (MPDSDM) is a Galaxy-based, open source disease-specific web portal for diabetes. It consists of three modules namely (i) data library (ii) data processing and (iii) data analysis tools. The data library (target library and literature) module provide extensive and curated information about the genes involved in type 1 and type 2 diabetes onset and progression stage (available at http://www.mpds-diabetes.in). The database also contains information on drug targets, biomarkers, therapeutics and associated genes specific to type 1, and type 2 diabetes. A unique MPDS identification number has been assigned for each gene involved in diabetes mellitus and the corresponding card contains chromosomal data, gene information, protein UniProt ID, functional domains, druggability and related pathway information. One of the objectives of the web portal is to have an open source data repository that contains all information on diabetes and use this information for developing therapeutics to cure diabetes. We also make an attempt for computational drug repurposing for the validated diabetes targets. We performed virtual screening of 1455 FDA approved drugs on selected 20 type 1 and type 2 diabetes proteins using docking protocol and their biological activity was predicted using "PASS Online" server (http://www.way2drug.com/passonline) towards anti-diabetic activity, resulted in the identification of 41 drug molecules. Five drug molecules (which are earlier known for anti-malarial/microbial, anti-viral, anti-cancer, anti-pulmonary activities) were proposed to have a better repurposing potential for type 2 anti-diabetic activity and good binding affinity towards type 2 diabetes target proteins.

Structures and energetics of complexation of metal ions with ammonia, water, and benzene: A computational study.

Quantum chemical calculations have been performed at CCSD(T)/def2-TZVP level to investigate the strength and nature of interactions of ammonia (NH3 ), water (H2 O), and benzene (C6 H6 ) with various metal ions and validated with the available experimental results. For all the considered metal ions, a preference for C6 H6 is observed for dicationic ions whereas the monocationic ions prefer to bind with NH3 . Density Functional Theory-Symmetry Adapted Perturbation Theory (DFT-SAPT) analysis has been employed at PBE0AC/def2-TZVP level on these complexes (closed shell), to understand the various energy terms contributing to binding energy (BE). The DFT-SAPT result shows that for the metal ion complexes with H2 O electrostatic component is the major contributor to the BE whereas, for C6 H6 complexes polarization component is dominant, except in the case of alkali metal ion complexes. However, in case of NH3 complexes, electrostatic component is dominant for s-block metal ions, whereas, for the d and p-block metal ion complexes both electrostatic and polarization components are important. The geometry (M(+) -N and M(+) -O distance for NH3 and H2 O complexes respectively, and cation-π distance for C6 H6 complexes) for the alkali and alkaline earth metal ion complexes increases down the group. Natural population analysis performed on NH3 , H2 O, and C6 H6 complexes shows that the charge transfer to metal ions is higher in case of C6 H6 complexes.

Graphane versus graphene: a computational investigation of the interaction of nucleobases, aminoacids, heterocycles, small molecules (CO2, H2O, NH3, CH4, H2), metal ions and onium ions.

Graphane has emerged as a two-dimensional hydrocarbon with interesting physical properties and potential applications. Understanding the interaction of graphane with various molecules and ions is crucial to appreciate its potential applications. We investigated the interaction of nucleobases, aminoacids, saturated and unsaturated heterocycles, small molecules, metal ions and onium ions with graphane by using density functional theory calculations. The preferred orientations of these molecules and ions on the graphane surface have been analysed. The binding energies of graphane with these molecules have been compared with the corresponding binding energies of graphene. Our results reveal that graphane forms stable complexes with all the molecules and ions yet showing lesser binding affinity when compared to graphene. As an exemption, the preferential strong binding of H2O with graphane than graphene reveals the fact that graphane is more hydrophilic than graphene. Charge transfer between graphane and the molecules and ions have been found to be an important factor in determining the binding strength of the complexes. The effect of the interaction of these molecules and ions on the HOMO-LUMO energy gap of graphane has also been investigated.

A computational investigation and the conformational analysis of dimers, anions, cations, and zwitterions of L-phenylalanine.

The structure and stability of various conformations of L-phenylalanine (PheN) and its zwitterions (PheZ), along with their ionized counterparts, cation (PheC) and anion (PheA), generated by adding and removing a proton respectively, have been investigated using first principle calculations in vacuum and in solution. This is followed by an extensive study on various possible dimer (PheD) conformations, which are noncovalently bound units without a peptide bond. This study results in 52, 31, 12, 9, and 11 minimum energy structures on the potential energy surfaces of PheD, PheN, PheC, PheA, and PheZ, respectively. Several important nonbonded interactions such as hydrogen bonds, NH-π, CH-π, OH-π, and π-π interactions, which impart stability to the monomeric and dimeric units, have been analyzed. The capability and strength of the nonbonded interactions drastically changing the conformational orientations of monomeric units has been illustrated.

Contrasting preferences of N and P substituted heteroaromatics towards metal binding: probing the regioselectivity of Li+ and Mg2+ binding to (CH)(6-m-n)N(m)P(n).

High level ab initio and hybrid DFT methods have been employed to investigate the interactions of metal ions (Li(+) and Mg(2+)) with N and P substituted six membered heteroaromatics (CH)(6-m-n)N(m)P(n). The binding energy (BE) of metal ions with the N and P substituted heteroaromatics has been computed at the CCSD(T)/cc-pVTZ//MP2/cc-pVTZ level with counterpoise correction. In the present study we systematically examined the preferential modes of binding of metal ions to the heteroaromatics. N-Substituted heteroaromatics show a strong preference for cation-σ mode of binding whereas the P-substituted heteroaromatics prefer cation-π mode of binding with the metal ions. Energy decomposition analysis (EDA) using the DFT-SAPT scheme has been carried out to analyse the contribution of various energy components to the BE. The results illustrate that for the cation-π complexes, the contribution of the induction term is more whereas in the case of cation-σ there is a competition between induction and electrostatic terms in the interaction energy.

Artificial intelligence in virtual screening: Models versus experiments.

A typical drug discovery project involves identifying active compounds with significant binding potential for selected disease-specific targets. Experimental high-throughput screening (HTS) is a traditional approach to drug discovery, but is expensive and time-consuming when dealing with huge chemical libraries with billions of compounds. The search space can be narrowed down with the use of reliable computational screening approaches. In this review, we focus on various machine-learning (ML) and deep-learning (DL)-based scoring functions developed for solving classification and ranking problems in drug discovery. We highlight studies in which ML and DL models were successfully deployed to identify lead compounds for which the experimental validations are available from bioassay studies.

Chemoinformatics and Machine Learning Approaches for Identifying Antiviral Compounds.

Current pandemics propelled research efforts in unprecedented fashion, primarily triggering computational efforts towards new vaccine and drug development as well as drug repurposing. There is an urgent need to design novel drugs with targeted biological activity and minimum adverse reactions that may be useful to manage viral outbreaks. Hence an attempt has been made to develop Machine Learning based predictive models that can be used to assess whether a compound has the potency to be antiviral or not. To this end, a set of 2358 antiviral compounds were compiled from the CAS COVID-19 antiviral SAR dataset whose activity was reported based on IC50 value. A total 1157 two-dimensional molecular descriptors were computed among which, the most highly correlated descriptors were selected using Tree-based, Correlation-based and Mutual information-based feature selection methods. Seven Machine Learning algorithms i. e., Random Forest, XGBoost, Support Vector Machine, KNN, Decision Tree, MLP Classifier and Logistic Regression were benchmarked. The best performance was achieved by the models developed using Random Forest and XGBoost algorithms in all the feature selection methods. The maximum predictive accuracy of both these models was 88 % with internal validation. Whereas, with an external dataset, a maximum accuracy of 93.10 % for XGBoost and 100 % for Random Forest based model was achievable. Furthermore, the study demonstrated scaffold analysis of the molecules as a pragmatic approach to explore the importance of structurally diverse compounds in data driven studies.

Quinazolinone linked pyrrolo[2,1-c][1,4]benzodiazepine (PBD) conjugates: Design, synthesis and biological evaluation as potential anticancer agents.

A series of novel quinazolinone linked pyrrolobenzodiazepine (PBD) conjugates were synthesized. These compounds 4a-f and 5a-f were prepared in good yields by linking C-8 of DC-81 with quinazolinone moiety through different alkane spacers. These conjugates were tested for anticancer activity against 11 human cancer cell lines and found to be very potent anticancer agents with GI(50) values in the range of <0.1-26.2microM. Among all the PBD conjugates, one of the conjugate 5c was tested against a panel of 60 human cancer cells. This compound showed activity for individual cancer cell lines with GI(50) values of <0.1microM. The thermal denaturation studies exhibited effective DNA binding ability compared to DC-81 and these results are further supported by molecular modeling studies. The detailed biological aspects of these conjugates on A375 cell line were studied. It was observed that compounds 4b and 5c induced the release of cytochrome c, activation of caspase-3, cleavage of PARP and subsequent cell death. Further, these compounds when treated with A375 cells showed the characteristic features of apoptosis like enhancement in the levels of p53, p21 and p27 inhibition of cyclin dependent kinase-2 (CDK2) and suppression of NF-kappaB. Moreover, these two compounds 4b and 5c control the cell proliferation by regulating anti-apoptotic genes like (B-cell lymphoma 2) Bcl-2. Therefore, the data generated suggests that these PBD conjugates activate p53 and inhibit NF-kappaB and thereby these compounds could be promising anticancer agents with better therapeutic potential for the suppression of tumours.

Elucidating the preference of dimeric over monomeric form for thermal stability of Thermus thermophilus isopropylmalate dehydrogenase: A molecular dynamics perspective.

An oligomer usually refers to a macromolecular complex formed by non-covalent interactions of monomers. Several thermophilic proteins are oligomers. The significance of oligomerization of individual proteins for stability at higher temperature is of prime importance for understanding evolution and increasing industrial productivity. The functional form of Thermus thermophilius isopropylmalate dehydrogenase (IPMDH), a widely studied protein to understand the factors affecting the thermal stability of a protein is a dimer, a simplest oligomer. To decipher the relationship between the effects of oligomerization on thermal stability of a protein, we have applied all-atom molecular mechanics approach by analyzing how temperature effects dynamics of a subunit in the presence and absence of another subunit in dimeric (SS) and monomeric forms (SA), respectively, before its denaturation begins. Comparing the difference in overall dynamic structural aspects at two different temperatures, 300 K and 337 K. Analysis of root mean square deviation (RMSD), root mean square fluctuations (RMSF) and Cα-Cα distance with an increase in temperature from 300 K to 337 K for a total of 0.2 µs reveals higher thermal stability of the dimer as compared to monomer. In contrast to dimeric form, the monomer is relatively stable at 300 K but cannot withstand the structural stability at 337 K leading to loosening of intramolecular interactions with maximum fluctuation at B23-B24 within a subunit. Energetic and structural properties indicate that B24-B24' is the major contributor to maintaining subunit-subunit interaction at 337 K. Correlation between the favorable interaction energy (IE) with the minimal perturbance in Cα atoms of domain 2 in a subunit in the presence of another subunit enhances the rigidity of the domain with subunit-subunit interaction. Overall, the study indicates that the dimeric over monomeric form enhances the protein's thermal stability and not all major subunit interacting regions contribute equally in maintaining the former.

A QSAR and molecular modelling study towards new lead finding: polypharmacological approach to Mycobacterium tuberculosis.

Developing effective inhibitors against Mycobacterium tuberculosis (Mtb) is a challenging task, primarily due to the emergence of resistant strains. In this study, we have proposed and implemented an in silico guided polypharmacological approach, which is expected to be effective against resistant strains by simultaneously inhibiting several potential Mtb drug targets. A combination of pharmacophore and QSAR based virtual screening strategy taking three key targets such as InhA (enoyl-acyl-carrier-protein reductase), GlmU (N-acetyl-glucosamine-1-phosphate uridyltransferase) and DapB (dihydrodipicolinate reductase) have resulted in initial 784 hits from Asinex database of 435,000 compounds. These hits were further subjected to docking with 33 Mtb druggable targets. About 110 potential polypharmacological hits were taken by integrating the aforementioned screening protocols. Further screening was conducted by taking various parameters and properties such as cell permeability, drug-likeness, drug-induced phospholipidosisand structural alerts. A consensus analysis has yielded 59 potential hits that pass through all the filters and can be prioritized for effective drug-resistant tuberculosis. This study proposes about nine potential hits which are expected to be promising molecules, having not only drug-like properties, but also being effective against multiple Mtb targets.

Modeling the permeability of drug-like molecules through the cell wall of Mycobacterium tuberculosis: an analogue based approach.

The emergence of drug resistant strains of Mycobacterium Tuberculosis (Mtb) accentuates the urgent need for the development of novel antitubercular drugs. The major causes of drug resistance are genetic mutations, the influx-efflux transporter system, and the complex cell wall system of Mtb, which can function as permeability barriers. The driving force for permeability of small molecules through a biological system depends on various physicochemical factors. To understand the permeability of small molecules and subsequent cell inhibition, we have developed predictive QSAR models based on reported enzyme-based (IC50) and cell-based (MIC) Mtb inhibitory data. The compounds that are highly active in enzyme-based assays and have significant variation in cell-based assays are assumed to possess the required permeability through the Mtb cell wall. The obtained models suggest the importance of molecular connectivity, lipophilicity (log P, size, shape), electrotopology (relative atomic mass, polarizability, electronegativity, ionization potential, atomic charges, van der Waals volume, hybridization, hydrogen bond acceptors/donors, number of fused rings) and functional groups (hydroxyl groups, primary and secondary amines) of a molecule in determining both its inhibitory potency and Mtb cell permeability. The models were validated with known Mtb inhibitors (9804) collected from the ChEMBL database, Mtb drugs (27) and clinical candidates (5). Further, these validated models were used to screen and prioritize a large database of compounds, including Zinc (152 128), Asinex (435 215), DrugBank (6531) and antimicrobial compounds (1324). The results obtained from 2D-QSAR analysis could improve our understanding towards Mtb cell permeability, which may aid in the rational design of novel potent molecules for tuberculosis (TB).

Structural and Functional Diversities of the Hexadecahydro-1H-cyclopenta[a]phenanthrene Framework, a Ubiquitous Scaffold in Steroidal Hormones.

Hexadecahydro-1H-cyclopenta[a]phenanthrene framework (HHCPF) has been considered as one of the privileged scaffolds due to its versatile presence in many biologically essential molecules. In our quest to unravel the privileged nature of this framework, we undertook a systematic analysis of target binding and Absorption, Distribution, Metabolism, Elimination, Toxicity (ADMET)/physicochemical properties of 110 drugs containing HHCPF reported in DrugBank. Effect of number and positions of double bonds in the framework and substitutions at each carbon position on the target selectivity as well as drug like properties of these drugs were studied. Fifteen different scaffolds based on the numbers and positions of double bonds in the HHCPF were identified among these drugs. The optimum number of double bonds present in the HHCPF scaffolds was observed to be one to three, and one particular positional isomer is predominant among many scaffolds with same numbers of double bonds. Docking studies reveal the role of substituents at different positions to make specific interactions with their respective targets. Based on the docking interactions, we proposed structure based e-Pharmacophore models for seven important targets of HHCPF drugs. Good correlations were observed between the substitutions carbon positions 3 and 17 of the scaffolds and ADMET properties of the HHCPF drugs. This work enables preliminary prediction of the target selectivity and ADMET properties of a new HHCPF molecule based on the scaffold, substituents and the pharmacophoric features.

Effect of alkyl substitution on H-bond strength of substituted amide-alcohol complexes.

The effect of alkyl substitution (CH3, C2H5, n-C3H7, i-C3H7, and t-C4H9) on the hydrogen bond strengths (H-bond) of substituted amide-alcohol complexes has been systematically explored. B3LYP/aug-cc-pVDZ method was applied to a total of 215 alkyl substituted amide-alcohol complexes to delineate the effect of substitution on the H-bond strength; formamide-water complex is taken as reference point. Complexes are classified into five types depending on the hydrogen donor, acceptor and the site of alkyl substitution (Type-IA, Type-IIA, Type-IB, Type-IIB and Type-III). The strength of H-bond was correlated with geometrical parameters such as proton-acceptor (H∙∙∙∙Y) distance, the length of proton donating bond (X-H). In all the complexes N-H and O-H stretching frequencies are red-shifted. The effect of alkyl substitution on N-H and O-H stretching frequencies were analyzed. Topological parameters like electron density at H∙∙∙∙Y and X-H bond critical points as derived from atom in molecules (AIM) theory was also evaluated. When C = O group is participating in H-bond, the strength of H-bond decreases with increasing size of alcohols except for methanol (Type-IA, Type-III and Type-IB complexes). But it increases with increasing size of alkyl groups on amide and decreases with bulky groups. In the case of N-H group as H-bond donor, the strength of H-bond increases with increasing size of alcohols (Type-IIA and Type-IIB complexes) whereas decreases with increasing size of alkyl groups on amide. Type-IA, IIA, IB and IIB complexes exhibit good correlations among IE, H-bond distance and electron density at bcp. In Type-III complexes, average H-bond distance and sum of electron densities shows better correlation with IEs than the corresponding individuals. The correlation of IE less with electron density at RCP compared to sum of electron densities.

Design of 1-arylsulfamido-2-alkylpiperazine derivatives as secreted PLA2 inhibitors.

Structure and analog based analysis of 3D-QSAR, CoMFA and CoMSIA, along with different docking protocols were used to evaluate the structure activity relationship of 26 analogues of 1-aryl sulfamido-2-alkyl piperazines to model the activities of group I and II secreted phospholipases A(2) (sPLA(2)s) and probe into the chemical space and nature of receptor--ligand interactions. The best CoMFA model yields cross-validated (q(2)) and conventional correlation coefficients (r(2)) of 0.703 and 0.962 respectively whereas CoMSIA model yields q(2) and r(2) values of 0.408 and 0.922 respectively, followed by docking analysis using FlexX and GOLD methodologies on the X-ray structure of human and bovine PLA(2)s. A comparative study was made to find out the differences in the active site residues of both PLA(2)s. The information enunciated from the analysis of CoMFA and CoMSIA maps and docking results were analyzed and employed in the design of 29 new ligands using molecules 4, 21, 22 from the initial set as templates. New ligands for group I and II secreted phospholipases A(2) (sPLA(2)s) have been thus designed based on the 32 analogues of 1-aryl sulfamido-2-alkyl piperazine with a cursory note on its synthetic feasibility. Molecular modeling studies indicate that the newly designed ligands are expected to show high affinity and experimental efforts in this direction is highly rewarding.

Towards design of the smallest planar tetracoordinate carbon and boron systems.

A series of cyclic hydrocarbons analogs where a carbon displays unusual planar tetracoordinate structure is proposed, employing hybrid density functional theory calculations using B3LYP functional and 6-311+G** basis set. Various strategies were employed to design the neutral planar tetracoordinate hydrocarbon analogs. The same strategy is employed for designing the planar tetracoordinate boron systems. The simplest neutral planar tetracoordinate hydrocarbons were proposed and the effect of substitution on their stability has been assessed. The aromatic stabilization is gauged with nucleus independent chemical shift calculations. The activation barriers for the ring opening reaction, the highest occupied molecular orbital and lowest unoccupied molecular orbitals gap and singlet-triplet energy difference were estimated to gauge the plausibility experimental realization.