Due to the diligence of inherent redundancy and robustness in many biological networks and pathways, multitarget inhibitors present a new prospect in the pharmaceutical industry for treatment of complex diseases. Nevertheless, to design multitarget inhibitors is concurrently a great challenge for medicinal chemists. We have developed a novel computational approach by integrating the affinity predictions from structure-based virtual screening with dual ligand-based pharmacophore to discover potential dual inhibitors of human Thymidylate synthase (hTS) and human dihydrofolate reductase (hDHFR). These are the key enzymes in folate metabolic pathway that is necessary for the biosynthesis of RNA, DNA, and protein. Their inhibition has found clinical utility as antitumor, antimicrobial, and antiprotozoal agents. A druglike database was utilized to perform dual-target docking studies. Hits identified through docking experiments were mapped over a dual pharmacophore which was developed from experimentally known dual inhibitors of hTS and hDHFR. Pharmacophore mapping procedure helped us in eliminating the compounds which do not possess basic chemical features necessary for dual inhibition. Finally, three structurally diverse hit compounds that showed key interactions at both active sites, mapped well upon the dual pharmacophore, and exhibited lowest binding energies were regarded as possible dual inhibitors of hTS and hDHFR. Furthermore, optimization studies were performed for final dual hit compound and eight optimized dual hits demonstrating excellent binding features at target systems were also regarded as possible dual inhibitors of hTS and hDHFR. In general, the strategy used in the current study could be a promising computational approach and may be generally applicable to other dual target drug designs.

Aim: Recent evidence suggests that aldo-keto reductase family 1 B10 (AKR1B10) may be a potential diagnostic or prognostic marker of human tumors, and that AKR1B10 inhibitors offer a promising choice for treatment of many types of human cancers. The aim of this study was to identify novel chemical scaffolds of AKR1B10 inhibitors using in silico approaches. Methods: The 3D QSAR pharmacophore models were generated using HypoGen. A validated pharmacophore model was selected for virtual screening of 4 chemical databases. The best mapped compounds were assessed for their drug-like properties. The binding orientations of the resulting compounds were predicted by molecular docking. Density functional theory calculations were carried out using B3LYP. The stability of the protein-ligand complexes and the final binding modes of the hit compounds were analyzed using 10 ns molecular dynamics (MD) simulations. Results: The best pharmacophore model (Hypo 1) showed the highest correlation coefficient (0.979), lowest total cost (102.89) and least RMSD value (0.59). Hypo 1 consisted of one hydrogen-bond acceptor, one hydrogen-bond donor, one ring aromatic and one hydrophobic feature. This model was validated by Fischer's randomization and 40 test set compounds. Virtual screening of chemical databases and the docking studies resulted in 30 representative compounds. Frontier orbital analysis confirmed that only 3 compounds had sufficiently low energy band gaps. MD simulations revealed the binding modes of the 3 hit compounds: all of them showed a large number of hydrogen bonds and hydrophobic interactions with the active site and specificity pocket residues of AKR1B10. Conclusion: Three compounds with new structural scaffolds have been identified, which have stronger binding affinities for AKR1B10 than known inhibitors.

Substitution of Cys for Ser at amino acid location 150 of the α-helix of 2-Cys Prx A regulates/enhances the dual enzymatic functions of the 2-Cys Prx A protein. If confirmed in planta, this leads to the potential for it to be used to maximize the functional utility of 2-Cys Prx A protein for improved metabolic functions and stress resistance in plants.

Human chymase catalyzes the hydrolysis of peptide bonds. Three chymase inhibitors with very similar chemical structures but highly different inhibitory profiles towards the hydrolase function of chymase were selected with the aim of elucidating the origin of disparities in their biological activities. As a substrate (angiotensin-I) bound crystal structure is not available, molecular docking was performed to dock the substrate into the active site. Molecular dynamics simulations of chymase complexes with inhibitors and substrate were performed to calculate the binding orientation of inhibitors and substrate as well as to characterize conformational changes in the active site. The results elucidate details of the 3D chymase structure as well as the importance of K40 in hydrolase function. Binding mode analysis showed that substitution of a heavier Cl atom at the phenyl ring of most active inhibitor produced a great deal of variation in its orientation causing the phosphinate group to interact strongly with residue K40. Dynamics simulations revealed the conformational variation in region of V36-F41upon substrate and inhibitor binding induced a shift in the location of K40 thus changing its interactions with them. Chymase complexes with the most activecompound and substrate were used for development of a hybrid pharmacophore model which was applied in databases screening. Finally, hits which bound well at the active site, exhibited key interactions and favorable electronic properties were identified as possible inhibitors for chymase. This study not only elucidates inhibitory mechanism of chymase inhibitors but also provides key structural insights which will aid in the rational design of novel potent inhibitors of the enzyme. In general, the strategy applied in the current study could be a promising computational approach and may be generally applicable to drug design for other enzymes.

Sirtuin belongs to a family of typical histone deacetylase which regulates the fundamental cellular biological processes including gene expression, genome stability, mitosis, nutrient metabolism, aging, mitochondrial function, and cell motility. Michael et. al. reported that B-site mutation (Q167A and H187A) decreased the SIRT2 activity but still the structural changes were not reported. Hence, we performed 5 ns molecular dynamics (MD) simulation on SIRT2 Apo-form and complexes with substrate/NAD+ and inhibitor of wild type (WT), Q167A, and H187A. The results revealed that the assembly and disassembly of C-site induced by presence of substrate/NAD+ and inhibitor, respectively. This assembly and disassembly was mainly due to the interaction between the substrate/NAD+ and inhibitor and F96 and the distance between F96 and H187 which are present at the neck of the C-site. MD simulations suggest that the conformational change of L3 plays a major role in assembly and disassembly of C-site. Our current results strongly suggest that the distinct conformational change of L3 as well as the assembly and disassembly of C-site plays an important role in SIRT2 deacetylation function. Our study unveiled the structural changes of SIRT2 in presence of NAD+ and inhibitor which should be helpful to improve the inhibitory potency of SIRT2.

HDAC8 inhibitors have become an attractive treatment for cancer. This study aimed to facilitate the identification of potential chemical scaffolds for the selective inhibition of histone deacetylase 8 (HDAC8) using in silico approaches. Non-linear QSAR classification and regression models of HDAC8 inhibitors were developed with support vector machine. Mean impact value-based sequential forward feature selection and grid search strategy were used for molecular descriptor selection and parameter optimization, respectively. The generated QSAR models were validated by leave-one-out cross validation and an external test set. The best QSAR classification model yielded 84 % of accuracy on the external test prediction and Matthews correlation coefficient is 0.69. The best QSAR regression model showed low root-mean-square error (0.63) and high squared correlation coefficient (0.53) for the test set. The validated QSAR models together with various drug-like properties, molecular docking and molecular dynamics simulation were sequentially used as a multi-step query in chemical database virtual screening. Finally, two hit compounds were discovered as new structural scaffolds which can be used for further in vitro and in vivo activity analyses. The strategy used in this study could be a promising computational strategy which can be utilized for other target drug design.

After G protein-coupled (GPC) receptors, protein kinases are considered as most important drug targets. Kinase family consists of multigene, which is particularly relevant to various diseases. Protein phosphorylation by kinases plays a crucial activity in many cellular processes like apoptosis, cell division, survival, metabolism, etc. The emergence of various protein kinases crystal structures from many research groups gives a deep insight to understand the catalysis and regulation of different protein kinases. This review will mainly focus on the active site structures and functions of few kinases related to different families such as Protein A, G, and C kinase family (AGC), Ca 2+ /Calmodulin-dependent kinase family (CaMK), Cyclin-dependent kinase family (CMGC), Receptor guanylatecyclase family (RGC), Tyrosine kinase family (TK), Tyrosine kinase-like family (TKL), Sterile 20 Serine/threonine kinase family (STE), and Casein kinase 1 family (CK1).

Off-target binding connotes the binding of a small molecule of therapeutic significance to a protein target in addition to the primary target for which it was proposed. Progressively such off-targeting is emerging to be regular practice to reveal side effects. Chymase is an enzyme of hydrolase class that catalyzes hydrolysis of peptide bonds. A link between heart failure and chymase is ascribed, and a chymase inhibitor is in clinical phase II for treatment of heart failure. However, the underlying mechanisms of the off-target effects of human chymase inhibitors are still unclear. Here, we develop a robust computational strategy that is applicable to any enzyme system and that allows the prediction of drug effects on biological processes. Putative off-targets for chymase inhibitors were identified through various structural and functional similarity analyses along with molecular docking studies. Finally, literature survey was performed to incorporate these off-targets into biological pathways and to establish links between pathways and particular adverse effects. Off-targets of chymase inhibitors are linked to various biological pathways such as classical and lectin pathways of complement system, intrinsic and extrinsic pathways of coagulation cascade, and fibrinolytic system. Tissue kallikreins, granzyme M, neutrophil elastase, and mesotrypsin are also identified as off-targets. These off-targets and their associated pathways are elucidated for the effects of inflammation, cancer, hemorrhage, thrombosis, and central nervous system diseases (Alzheimer's disease). Prospectively, our approach is helpful not only to better understand the mechanisms of chymase inhibitors but also for drug repurposing exercises to find novel uses for these inhibitors.