Structure based virtual screening of natural product molecules as glycosidase inhibitors

Objective of the present investigation comprised of the application of in silico methods to discover novel natural product (NP) based potential inhibitors for carbohydrate mediated diseases. Structure based drug design studies (molecular docking and structure based pharmacophore analysis)  were carried out on a series of natural product compounds to identify significant bioactive molecules to inhibit α-mannosidase (I and II) and β-galactosidase enzymes. Furthermore, protein ligand interaction fingerprint analysis, molecular dynamics simulations and molecular access system (MACCS) fingerprint analysis were performed to understand the binding behaviors of the studied molecules. The results derived from these analyses showed that the identified compounds exhibit significant binding interactions with the active site residues. The compounds, NP-51, NP-81 and NP-165 have shown significant docking score against the studied enzymes (α-mannosidases-I, α-mannosidases-II and β-galactosidases). The fingerprint studies showed that the presence of rings (aromatic or aliphatic) with sulfur atoms, nitrogen atoms, methyl groups, etc. have favorable effects on the α-mannosidase II inhibitory activity. However, the presence of halogen atoms substituted in the molecules have reduced inhibitory ability against α-mannosidase II. The compound, NP-165 has significant activity against both enzymes (α-mannosidases and β-galactosidases). These studies accomplished that the compounds identified through in silico methodologies can be used to develop semisynthetic derivatives of the glycosidase inhibitors and can be screened for the treatment of different carbohydrate mediated diseases.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-021-00115-9.

In Silico Based Structural and Fingerprint Analysis of Structurally Diverse AT1 inhibitors

Background and Objective:

The development of pharmacologically active molecules for the treatment of hypertension and other cardiovascular diseases are important nowadays. In the present investigation, computational techniques have been implemented on Angiotensin II Type 1 (AT1) antagonists to develop better predictive models.

Methods:

Quantitative Structure Activity Relationship (QSAR) and structural patterns/fragments analyses were performed using physicochemical descriptors and MACCS Fingerprints calculaced from AT1 inhibitors collected from the literature.

Results:

The significant models developed have been validated by Leave One Out (LOO) and test set methods, which exhibit considerable Q2 values (>0.65 for the training set and >0.5 for the test set) and the R2pred values for the models are also >0.5. The applicability of the contributed descriptors in these models revealed that the chlorine atom, dipole moment, hydrogen bond donor atoms and electrostatic potential are negatively contributing, and the presence of bond between heavy atoms and the carbon atom connected with small side chain and topological polar vdW surface area are favorable for the AT1 antagonistic activity. The MACCS Fingerprints showed that the presence of atoms (kind of heavy atoms), such as N, O, and S, connected with other heteroatoms or carbon or any other atoms, through single or double bonds are predominantly present in highly active molecules. The presence of halogens, long chain alkanes, halogenated alkanes, and sulfur atoms attached with nitrogen through any atoms are responsible for decreased AT1 antagonistic activity.

Conclusion:

The results have provided additional information on the structural patterns of the compounds based on its MACCS Fingerprints, which may be used for further characterization and design of novel AT1 inhibitors.

Phomoidrides E–G, three dimeric anhydrides from the fungus Pleosporales sp. give new insight to the biosynthesis of phomoidrides

Three novel dimeric anhydrides with unprecedented skeletons, phomoidrides E–G, were isolated from the fungus Pleosporales sp. A new biosynthetic strategy for dimerization with a key Claisen-like intermediate M1 is proposed.

Considerations for Docking of Selective Angiotensin-Converting Enzyme Inhibitors

The angiotensin-converting enzyme (ACE) is a two-domain dipeptidylcarboxypeptidase, which has a direct involvement in the control of blood pressure by performing the hydrolysis of angiotensin I to produce angiotensin II. At the same time, ACE hydrolyzes other substrates such as the vasodilator peptide bradykinin and the anti-inflammatory peptide N-acetyl-SDKP. In this sense, ACE inhibitors are bioactive substances with potential use as medicinal products for treatment or prevention of hypertension, heart failures, myocardial infarction, and other important diseases. This review examined the most recent literature reporting ACE inhibitors with the help of molecular modeling. The examples exposed here demonstrate that molecular modeling methods, including docking, molecular dynamics (MD) simulations, quantitative structure-activity relationship (QSAR), etc, are essential for a complete structural picture of the mode of action of ACE inhibitors, where molecular docking has a key role. Examples show that too many works identified ACE inhibitory activities of natural peptides and peptides obtained from hydrolysates. In addition, other works report non-peptide compounds extracted from natural sources and synthetic compounds. In all these cases, molecular docking was used to provide explanation of the chemical interactions between inhibitors and the ACE binding sites. For docking applications, most of the examples exposed here do not consider that: (i) ACE has two domains (nACE and cACE) with available X-ray structures, which are relevant for the design of selective inhibitors, and (ii) nACE and cACE binding sites have large dimensions, which leads to non-reliable solutions during docking calculations. In support of the solution of these problems, the structural information found in Protein Data Bank (PDB) was used to perform an interaction fingerprints (IFPs) analysis applied on both nACE and cACE domains. This analysis provides plots that identify the chemical interactions between ligands and both ACE binding sites, which can be used to guide docking experiments in the search of selective natural components or novel drugs. In addition, the use of hydrogen bond constraints in the S₂ and S₂′ subsites of nACE and cACE are suggested to guarantee that docking solutions are reliable.

Structural insights into flavones as protein kinase CK2 inhibitors derived from a combined computational study

Binding conformation of flavone inhibitors to protein kinase CK2.