Showing papers by "Mohane Selvaraj Coumar published in 2015"

Evolutionary algorithms for de novo drug design - A survey

Abstract: In de novo drug design multiple pharmaceutically important parameters need to be optimized. Various tools using evolutionary algorithm, a soft computing technique for multi-objective optimization to find novel molecules for drug development are surveyed. De novo drug design supplies novel molecules for drug development.In de novo drug design multiple parameters are optimized.Evolutionary algorithms are used for multi-objective optimization.Evolutionary algorithms used in de novo drug design tools are analyzed here. The process of drug design and discovery demands several man years and huge investment. Computer-aided drug design (CADD) technique is an aid to speed up the drug discovery process. De novo drug design, a CADD technique to identify drug-like novel chemical structures from a huge chemical search space, helps to find new drugs by the optimization of multiple pharmaceutically relevant parameters required for a successful drug. As the search space is very large in the case of de novo drug design, evolutionary algorithm (EA), a soft computing technique can be used to find an optimal solution, which in this case is a novel drug. In this paper, various EA techniques used in de novo drug design tools are surveyed and analyzed in detail, with particular emphasis on the computational aspects.

Homology modeling of DFG-in FMS-like tyrosine kinase 3 (FLT3) and structure-based virtual screening for inhibitor identification

Abstract: The inhibition of FMS-like tyrosine kinase 3 (FLT3) activity using small-molecule inhibitors has emerged as a target-based alternative to traditional chemotherapy for the treatment of acute myeloid leukemia (AML). In this study, we report the use of structure-based virtual screening (SBVS), a computer-aided drug design technique for the identification of new chemotypes for FLT3 inhibition. For this purpose, homology modeling (HM) of the DFG-in FLT3 structure was carried using two template structures, including PDB ID: 1RJB (DFG-out FLT3 kinase domain) and PDB ID: 3LCD (DFG-in CSF-1 kinase domain). The modeled structure was able to correctly identify known DFG-in (SU11248, CEP-701, and PKC-412) and DFG-out (sorafenib, ABT-869 and AC220) FLT3 inhibitors, in docking studies. The modeled structure was then used to carry out SBVS of an HTS library of 125,000 compounds. The top scoring 97 compounds were tested for FLT3 kinase inhibition, and two hits (BPR056, IC50 = 2.3 and BPR080, IC50 = 10.7 μM) were identified. Molecular dynamics simulation and density functional theory calculation suggest that BPR056 (MW: 325.32; cLogP: 2.48) interacted with FLT3 in a stable manner and could be chemically optimized to realize a drug-like lead in the future.

Identification of ligand efficient, fragment-like hits from an HTS library: structure-based virtual screening and docking investigations of 2H- and 3H-pyrazolo tautomers for Aurora kinase A selectivity.

Abstract: Furanopyrimidine 1 (IC50 = 273 nM, LE = 0.36, LELP = 10.28) was recently identified by high-throughput screening (HTS) of an in-house library (125,000 compounds) as an Aurora kinase inhibitor. Structure-based hit optimization resulted in lead molecules with in vivo efficacy in a mouse tumour xenograft model, but no oral bioavailability. This is attributed to “molecular obesity”, a common problem during hit to lead evolution during which degradation of important molecular properties such as molecular weight (MW) and lipophilicity occurs. This could be effectively tackled by the right choice of hit compounds for optimization. In this regard, ligand efficiency (LE) and ligand efficiency dependent lipophilicity (LELP) indices are more often used to choose fragment-like hits for optimization. To identify hits with appropriate LE, we used a MW cut-off <250, and pyrazole structure to filter HTS library. Next, structure-based virtual screening using software (Libdock and Glide) in the Aurora A crystal structure (PDB ID: 3E5A) was carried out, and the top scoring 18 compounds tested for Aurora A enzyme inhibition. This resulted in the identification of a novel tetrahydro-pyrazolo-isoquinoline hit 7 (IC50 = 852 nM, LE = 0.44, LELP = 8.36) with fragment-like properties suitable for further hit optimization. Moreover, hit 7 was found to be selective for Aurora A (Aurora B IC50 = 35,150 nM) and the possible reasons for selectivity investigated by docking two tautomeric forms (2H- and 3H-pyrazole) of 7 in Auroras A and B (PDB ID: 4AF3) crystal structures. This docking study shows that the major 3H-pyrazole tautomer of 7 binds in Aurora A stronger than in Aurora B. A series of in silico filters were applied to HTS library compounds, followed by biochemical testing identified aurora A selective hit 7 with fragment-like characters suitable for further development.

Structural Biology Insight for the Design of Sub-type Selective Aurora Kinase Inhibitors.

Abstract: Aurora kinase A, B and C, are key regulators of mitosis and are over expressed in many of the human cancers, making them an ideal drug target for cancer chemotherapy. Currently, over a dozen of Aurora kinase inhibitors are in various phases of clinical development. The majority of the inhibitors (VX-680/MK-0457, PHA-739358, CYC116, SNS-314, AMG 900, AT-9283, SCH- 1473759, ABT-348, PF-03814735, R-763/AS-703569, KW-2449 and TAK-901) are pan-selective (isoform non-selective) and few are Aurora A (MLN8054, MLN8237, VX-689/MK5108 and ENMD 2076) and Aurora B (AZD1152 and GSK1070916) sub-type selective. Despite the intensive research efforts in the past decade, no Aurora kinase inhibitor has reached the market. Recent evidence suggests that the sub-type selective Aurora kinase A inhibitor could possess advantages over pan-selective Aurora inhibitors, by avoiding Aurora B mediated neutropenia. However, sub-type selective Aurora kinase A inhibitor design is very challenging due to the similarity in the active site among the isoforms. Structural biology and computational aspects pertaining to the design of Aurora kinase inhibitors were analyzed and found that a possible means to develop sub-type selective inhibitor is by targeting Aurora A specific residues (Leu215, Thr217 and Arg220) or Aurora B specific residues (Arg159, Glu161 and Lys164), near the solvent exposed region of the protein. Particularly, a useful strategy for the design of sub-type selective Aurora A inhibitor could be by targeting Thr217 residue as in the case of MLN8054. Further preclinical and clinical studies with the sub-type selective Aurora inhibitors could help bring them to the market for the treatment of cancer.

In Silico and In Vitro Investigation of the Piperineʼs Male Contraceptive Effect: Docking and Molecular Dynamics Simulation Studies in Androgen-Binding Protein and Androgen Receptor

Abstract: Understanding the molecular mechanism of action of traditional medicines is an important step towards developing marketable drugs from them. Piperine, an active constituent present in the Piper species, is used extensively in Ayurvedic medicines (practiced on the Indian subcontinent). Among others, piperine is known to possess a male contraceptive effect; however, the molecular mechanism of action for this effect is not very clear. In this regard, detailed docking and molecular dynamics simulation studies of piperine with the androgen-binding protein and androgen receptors were carried out. Androgen receptors control male sexual behavior and fertility, while the androgen-binding protein binds testosterone and maintains its concentration at optimal levels to stimulate spermatogenesis in the testis. It was found that piperine docks to the androgen-binding protein, similar to dihydrotestosterone, and to androgen receptors, similar to cyproterone acetate (antagonist). Also, the piperine-androgen-binding protein and piperine-androgen receptors interactions were found to be stable throughout 30 ns of molecular dynamics simulation. Further, two independent simulations for 10 ns each also confirmed the stability of these interactions. Detailed analysis of the piperine-androgen-binding protein interactions shows that piperine interacts with Ser42 of the androgen-binding protein and could block the binding with its natural ligands dihydrotestosterone/testosterone. Moreover, piperine interacts with Thr577 of the androgen receptors in a manner similar to the antagonist cyproterone acetate. Based on the in silico results, piperine was tested in the MDA-kb2 cell line using the luciferase reporter gene assay and was found to antagonize the effect of dihydrotestosterone at nanomolar concentrations. Further detailed biochemical experiments could help to develop piperine as an effective male contraceptive agent in the future.