Sree Kanth Sivan

Molecular docking and 3D-QSAR studies on inhibitors of DNA damage signaling enzyme human PARP-1

Poly (ADP-ribose) polymerase-1 (PARP-1) operates in a DNA damage signaling network. Molecular docking and three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on human PARP-1 inhibitors. Docked conformation obtained for each molecule was used as such for 3D-QSAR analysis. Molecules were divided into a training set and a test set randomly in four different ways, partial least square analysis was performed to obtain QSAR models using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Derived models showed good statistical reliability that is evident from their r2, q2loo and r2pred values. To obtain a consensus for predictive ability from all the models, average regression coefficient r2avg was calculated. CoMFA and CoMSIA models showed a value of 0.930 and 0.936, respectively. Information obtained from the best 3D-QSAR model was applied for optimization of lead molecule and design of novel potential inhibitors.

Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis – a case study on HIV-1 protease inhibitors

AbstractMultiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on 25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by applying leave one out cross validation method, rloo2 values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r2 values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined using a test set of 60 cyclic urea molecules that gave predictive correlation (rpred2) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information 25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave remarkable out come with rpred2 of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing 3D QSAR analysis on molecules having different structural motifs. FigureSchematic representation of the multiple receptor conformation docking, clustering and 3D QSAR. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) analysis is an exceptional tool for understanding the structure activity relations of molecules towards their biological activities. Receptor binding conformation of the molecule gives an added advantage to understand ligand receptor interactions required for bioactivity. There are different methods employed for obtaining the receptor based alignment of the molecules, but this method is limited to molecules having common substructure. Here we describe the new approach of multiple receptors conformation docking (MRCD) and clustering of dock poses that allows seamless incorporation of receptor binding conformation of the molecules on wide range of molecules with varied structural scaffold.

Molecular docking, 3D QSAR and dynamics simulation studies of imidazo-pyrrolopyridines as janus kinase 1 (JAK 1) inhibitors

Janus kinase 1 (JAK 1) plays a critical role in initiating responses to cytokines by the JAK-signal transducer and activator of transcription (JAK-STAT). This controls survival, proliferation and differentiation of a variety of cells. Docking, 3D quantitative structure activity relationship (3D-QSAR) and molecular dynamics (MD) studies were performed on a series of Imidazo-pyrrolopyridine derivatives reported as JAK 1 inhibitors. QSAR model was generated using 30 molecules in the training set; developed model showed good statistical reliability, which is evident from r2ncv and r2loo values. The predictive ability of this model was determined using a test set of 13 molecules that gave acceptable predictive correlation (r2Pred) values. Finally, molecular dynamics simulation was performed to validate docking results and MM/GBSA calculations. This facilitated us to compare binding free energies of cocrystal ligand and newly designed molecule R1. The good concordance between the docking results and CoMFA/CoMSIA contour maps afforded obliging clues for the rational modification of molecules to design more potent JAK 1 inhibitors.

Molecular docking and MM/GBSA integrated protocol for designing small molecule inhibitors against HIV-1 gp41

Human immunodeficiency virus type-1 (HIV-1) enters into the host cell using its non-covalently bonded envelope glycoproteins 120 and 41 (gp120 and gp41). HIV-1 gp41 plays an instrumental role in the membrane fusion and entry of viral genome into the host cytosol. Binding of virus to host cell receptors triggers a cascade of conformational changes in gp120 and gp41. During the fusion, core of gp41 comprising C-heptad repeat coils into the highly conserved, deep hydrophobic pocket of N-heptad repeat forming a six-helix bundle (6-HB). The apposition of the host cell membrane and viral membrane is initiated with the formation of 6-HB. The inhibition of 6-HB formation has been proved to be an effective way to thwart the viral and host cell fusion. In this work, we have performed computational study on 62 6-HB formation inhibitors reported in the literature. An integrated computational protocol using molecular docking and molecular mechanics/generalized born surface area calculations was employed to these known inhibitors to understand mode of interaction with receptor. Our study revealed reasonably good agreement between computational parameters and experimental inhibitory potentials of these molecules. The results encouraged us to design novel gp41 6-HB formation inhibitors.

Molecular modeling-driven approach for identification of Janus kinase 1 inhibitors through 3D-QSAR, docking and molecular dynamics simulations

Abstract Janus kinase 1 (JAK 1) belongs to the JAK family of intracellular nonreceptor tyrosine kinase. JAK-signal transducer and activator of transcription (JAK-STAT) pathway mediate signaling by cytokines, which control survival, proliferation and differentiation of a variety of cells. Three-dimensional quantitative structure activity relationship (3 D-QSAR), molecular docking and molecular dynamics (MD) methods was carried out on a dataset of Janus kinase 1(JAK 1) inhibitors. Ligands were constructed and docked into the active site of protein using GLIDE 5.6. Best docked poses were selected after analysis for further 3 D-QSAR analysis using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodology. Employing 60 molecules in the training set, 3 D-QSAR models were generate that showed good statistical reliability, which is clearly observed in terms of r2ncv and q2loo values. The predictive ability of these models was determined using a test set of 25 molecules that gave acceptable predictive correlation (r2Pred) values. The key amino acid residues were identified by means of molecular docking, and the stability and rationality of the derived molecular conformations were also validated by MD simulation. The good consonance between the docking results and CoMFA/CoMSIA contour maps provides helpful clues about the reasonable modification of molecules in order to design more efficient JAK 1 inhibitors. The developed models are expected to provide some directives for further synthesis of highly effective JAK 1 inhibitors.

Multiple-receptor conformation docking, dock pose clustering, and 3D QSAR-driven approaches exploring new HIV-1 RT inhibitors

Human immunodeficiency virus type-1 reverse transcriptase (HIV-1 RT) plays a key in the life cycle of HIV-1. It is considered to be one of the promising targets for treating HIV/AIDS which contains two drug binding sites, a substrate binding site, and an allosteric site. Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are a class of RT inhibitors that bind to allosteric sites on HIV-1 RT in a non-competitive manner and thereby disrupting the conformation of RT. Hence, they can act as potent inhibitors against HIV-1 RT. In present study, the key structural requirements for enhancing HIV-1 RT inhibitory activity were explored from combined docking and three-dimensional quantitative structure activity relationship (3D QSAR) protocols. Initially, multiple-receptor conformation docking (MRCD) was performed using a series of diaryl pyridine and pyrimidine derivatives into the active site of ten X-ray crystal structures and one NMR-resolved conformation of HIV-1 RT. Later, the dock poses obtained from docking were clustered and 3D QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods. Finally, a robust model was established using cross-validation techniques and the robustness of the model was confirmed through high accuracy of q2loo of 0.843 and 0.682, r2ncv of 0.977 and 0.949, and r2pred of 0.702 and 0.690, respectively, for CoMFA and CoMSIA. Based on the outcome of the results, new pyrimidine derivatives having potential inhibitory against HIV-1 RT were designed.

Molecular docking, MM/GBSA and 3D-QSAR studies on EGFR inhibitors

AbstractEpidermal growth factor receptor (EGFR) is the first growth factor receptor proposed as a target for cancer therapy. Molecular modeling protocols like molecular docking, molecular mechanics/generalized born surface area (MM/GBSA) calculations and three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on 45 molecules to understand the structural requirements for EGFR tyrosine kinase inhibitors. Conformation for all the molecules obtained from molecular docking were used as is for 3D-QSAR analysis. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were obtained by performing partial least square analysis on 35 training molecules and these models were validated using 10 test moleucles. The models showed good statistical results in terms of r 2, qloo2

3D QSAR based design of novel oxindole derivative as 5HT7 inhibitors.

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Structural insights of Staphylococcus aureus FtsZ inhibitors through molecular docking, 3D-QSAR and molecular dynamics simulations

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Rational design of methicillin resistance staphylococcus aureus inhibitors through 3D-QSAR, molecular docking and molecular dynamics simulations.

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