Comparing molecular dynamics-derived pharmacophore models with docking: A study on CDK-2 inhibitors

Culletta, Giulia; Almerico, Anna Maria; Tutone, Marco

doi:10.1016/j.cdc.2020.100485

Cited by 7 publications

(6 citation statements)

References 38 publications

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“…For the newly added pharmacophore features, the tolerance radius was increased by 0.15 Å to compensate for small deviations in the 3D coordinates. The computational details are reported in previously published papers [51,52]…”

Section: Myshape Approachmentioning

confidence: 99%

“…The residues that characterized the The pharmacophore features were decreased to five, the two hydrophobic features on the naphthyl ring of BIBR1532 were fused into one, and the tolerance radius for the new pharmacophore feature was increased by 0.15 Å to compensate for small deviations (Figure 1B). To improve the performance of the virtual screening (VS) process, the recent MYSHAPE (Molecular dYnamics SHared PharmacophorE) approach was used [51,52]. According to this approach, the exploration of the protein conformations by molecular dynamics coupled with the pharmacophore modeling improved the result of the VS concerning the corresponding model generated from the PDB coordinates set.…”

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confidence: 99%

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In Silico Design, Synthesis, and Biological Evaluation of Anticancer Arylsulfonamide Endowed with Anti-Telomerase Activity

et al. 2022

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Telomerase, a reverse transcriptase enzyme involved in DNA synthesis, has a tangible role in tumor progression. Several studies have evidenced telomerase as a promising target for developing cancer therapeutics. The main reason is due to the overexpression of telomerase in cancer cells (85–90%) compared with normal cells where it is almost unexpressed. In this paper, we used a structure-based approach to design potential inhibitors of the telomerase active site. The MYSHAPE (Molecular dYnamics SHared PharmacophorE) approach and docking were used to screen an in-house library of 126 arylsulfonamide derivatives. Promising compounds were synthesized using classical and green methods. Compound 2C revealed an interesting IC50 (33 ± 4 µM) against the K-562 cell line compared with the known telomerase inhibitor BIBR1532 IC50 (208 ± 11 µM) with an SI ~10 compared to the BALB/3-T3 cell line. A 100 ns MD simulation of 2C in the telomerase active site evidenced Phe494 as the key residue as well as in BIBR1532. Each moiety of compound 2C was involved in key interactions with some residues of the active site: Arg557, Ile550, and Gly553. Compound 2C, as an arylsulfonamide derivative, is an interesting hit compound that deserves further investigation in terms of optimization of its structure to obtain more active telomerase inhibitors

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Section: Myshape Approachmentioning

confidence: 99%

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confidence: 99%

In Silico Design, Synthesis, and Biological Evaluation of Anticancer Arylsulfonamide Endowed with Anti-Telomerase Activity

et al. 2022

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“…In recent years, the constant update of hardware capabilities allowed the development of enhanced MD methods able to provide a full dynamical description of the target–ligand-binding events [ 14 ]. These methods are usually employed given that the sampling issue is fundamental to describing these slow processes while docking methods continue to be pivotal to screening large libraries, also assisted by MD [ 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Immunoproteasome and Non-Covalent Inhibition: Exploration by Advanced Molecular Dynamics and Docking Methods

et al. 2021

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The selective inhibition of immunoproteasome is a valuable strategy to treat autoimmune, inflammatory diseases, and hematologic malignancies. Recently, a new series of amide derivatives as non-covalent inhibitors of the β1i subunit with Ki values in the low/submicromolar ranges have been identified. Here, we investigated the binding mechanism of the most potent and selective inhibitor, N-benzyl-2-(2-oxopyridin-1(2H)-yl)propanamide (1), to elucidate the steps from the ligand entrance into the binding pocket to the ligand-induced conformational changes. We carried out a total of 400 ns of MD-binding analyses, followed by 200 ns of plain MD. The trajectories clustering allowed identifying three representative poses evidencing new key interactions with Phe31 and Lys33 together in a flipped orientation of a representative pose. Further, Binding Pose MetaDynamics (BPMD) studies were performed to evaluate the binding stability, comparing 1 with four other inhibitors of the β1i subunit: N-benzyl-2-(2-oxopyridin-1(2H)-yl)acetamide (2), N-cyclohexyl-3-(2-oxopyridin-1(2H)-yl)propenamide (3), N-butyl-3-(2-oxopyridin-1(2H)-yl)propanamide (4), and (S)-2-(2-oxopyridin-1(2H)-yl)-N,4-diphenylbutanamide (5). The obtained results in terms of free binding energy were consistent with the experimental values of inhibition, confirming 1 as a lead compound of this series. The adopted methods provided a full dynamic description of the binding events, and the information obtained could be exploited for the rational design of new and more active inhibitors.

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“…Molecular dynamics (MD) based pharmacophore models have emerged as quite powerful tools which not only account for the flexibility of the target(s), but also help to identify novel key interaction features in the binding sites (Spyrakis et al, 2015) which is otherwise unexplored in the crystal structures and may be harnessed to design new inhibitors (Choudhury et al, 2014(Choudhury et al, , 2015Choudhury and Bhardwaj, 2020;Guterres and Im, 2020). Literature reports several studies that have used molecular dynamics to sample huge number of receptor conformations and generated pharmacophore models from these conformations which showed improved enrichment for specific interaction features (Bottegoni et al, 2011;Wieder et al, 2016;Culletta et al, 2020). MD simulations combined with virtual screening of compound libraries have led to identification of biologically active compounds for several targets.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Dynamic Pharmacophore Models as Effective Tools to Identify Novel Chemotypes for Anti-TB Inhibitor Design: A Case Study With Mtb-DapB

Choudhury

Bhardwaj

2020

Front. Chem.

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Antimicrobial resistance (AMR) is one of the most serious global public health threats as it compromises the successful treatment of deadly infectious diseases like tuberculosis. New therapeutics are constantly needed but it takes a long time and is expensive to explore new biochemical space. One way to address this issue is to repurpose the validated targets and identify novel chemotypes that can simultaneously bind to multiple binding pockets of these targets as a new lead generation strategy. This study reports such a strategy, dynamic hybrid pharmacophore model (DHPM), which represents the combined interaction features of different binding pockets contrary to the conventional approaches, where pharmacophore models are generated from single binding sites. We have considered Mtb-DapB, a validated mycobacterial drug target, as our model system to explore the effectiveness of DHPMs to screen novel unexplored compounds. Mtb-DapB has a cofactor binding site (CBS) and an adjacent substrate binding site (SBS). Four different model systems of Mtb-DapB were designed where, either NADPH/NADH occupies CBS in presence/absence of an inhibitor 2, 6-PDC in the adjacent SBS. Two more model systems were designed, where 2, 6-PDC was linked to NADPH and NADH to form hybrid molecules. The six model systems were subjected to 200 ns molecular dynamics simulations and trajectories were analyzed to identify stable ligand-receptor interaction features. Based on these interactions, conventional pharmacophore models (CPM) were generated from the individual binding sites while DHPMs were created from hybrid-molecules occupying both binding sites. A huge library of 1,563,764 publicly available molecules were screened by CPMs and DHPMs. The screened hits obtained from both types of models were compared based on their Hashed binary molecular fingerprints and 4-point pharmacophore fingerprints using Tanimoto, Cosine, Dice and Tversky similarity matrices. Molecules screened by DHPM exhibited significant structural diversity, better binding strength and drug like properties as compared to the compounds screened by CPMs indicating the efficiency of DHPM to explore new chemical space for anti-TB drug discovery. The idea of DHPM can be applied for a wide range of mycobacterial or other pathogen targets to venture into unexplored chemical space.

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Comparing molecular dynamics-derived pharmacophore models with docking: A study on CDK-2 inhibitors

Cited by 7 publications

References 38 publications

In Silico Design, Synthesis, and Biological Evaluation of Anticancer Arylsulfonamide Endowed with Anti-Telomerase Activity

In Silico Design, Synthesis, and Biological Evaluation of Anticancer Arylsulfonamide Endowed with Anti-Telomerase Activity

Immunoproteasome and Non-Covalent Inhibition: Exploration by Advanced Molecular Dynamics and Docking Methods

Hybrid Dynamic Pharmacophore Models as Effective Tools to Identify Novel Chemotypes for Anti-TB Inhibitor Design: A Case Study With Mtb-DapB

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