Journal of Computational Biophysics and Chemistry

The notable ability of human liver cytochrome P450 3A4 (CYP3A4) to metabolize diverse xenobiotics encourages researchers to explore in-depth the mechanism of enzyme action. Numerous CYP3A4 protein crystal structures have been deposited in protein data bank (PDB) and are majorly used in molecular docking analysis. The quality of the molecular docking results depends on the three-dimensional CYP3A4 protein crystal structures from the PDB. Present review endeavors to provide a brief outline of some technical parameters of CYP3A4 PDB entries as valuable information for molecular docking research. PDB entries between 22 April 2004 and 2 June 2021 were compiled and the active sites were thoroughly observed. The present review identified 76 deposited PDB entries and described basic information that includes CYP3A4 from human genetic, Escherichia coli (E. coli) use for protein expression, crystal structure obtained from X-ray diffraction method, taxonomy ID 9606, Uniprot ID P08684, ligand–protein structure description, co-crystal ligand, protein site deposit and resolution ranges between 1.7Å and 2.95Å. The observation of protein–ligand interactions showed the various residues on the active site depending on the ligand. The residues Ala305, Ser119, Ala370, Phe304, Phe108, Phe213 and Phe215 have been found to frequently interact with ligands from CYP3A4 PDB. Literature surveys of 17 co-crystal ligands reveal multiple mechanisms that include competitive inhibition, noncompetitive inhibition, mixed-mode inhibition, mechanism-based inhibition, substrate with metabolite, inducer, or combination modes of action. This overview may help researchers choose a trustworthy CYP3A4 protein structure from the PDB database to apply the protein in molecular docking analysis for drug discovery.

The glucose-6-phosphate dehydrogenase (G6PD) enzyme plays a vital role in converting glucose-6-phosphate (G6P) to 6-phosphogluconolactone, as well as in reducing NADP($+$) to NADPH. The Asp/His moiety of G6PD acts as a catalytic dyad in the active site of G6PD. This catalytic mechanism describes erythrocyte protection from oxidative stress and prevention of hemolysis; hence their exact understanding is important in the normal functioning of red blood cells. Herein, computational investigations were carried out to describe a plausible mechanism of the G6PD enzyme by using a series of DFT theoretical calculations using the M06-2X/6-31G ($d$, $p$) basis set and performed in the following three discrete steps: (i) Proton transfer from His309 to Asp246, (ii) A subsequent proton transfer from G6P to His309, and (iii) A rate-limiting hydride transfer that reduces NADP($+$) to NADPH. The final overall mechanism, therefore, results in the production of phosphogluconolactone and NADPH. The DFT calculations indicate that, in the absence of the His/Asp dyad, the chemical reaction changes from a low-energy sequential mechanism to the proposed concurrent mechanism with a very high energy barrier ($E_{\mathrm{\text{rel}}}=76.6$kcalmol${}^{-1}$). These results show that the Asp246 residue is responsible for transforming a high energy concurrent reaction into a low energy multistep sequential reaction in the G6PD enzyme for the production of NADPH. This work supports the study and design of the mechanism-based inhibitors and provides a detailed understanding of the catalytic mechanism of the enzyme thereby opening new possibilities towards an understanding of controlling detoxification processes due to premature breaking in red blood cells.

Vanadium haloperoxidases play an important catalytic role in the natural production of antibiotics which are difficult to make in the laboratory. Understanding the catalytic mechanism of these enzymes will aid in the production of artificial enzymes useful in bioengineering the synthesis of drugs and useful chemicals. However, the catalytic mechanism remains not fully understood yet. In this paper, we investigate one of the key steps of the catalytic mechanism using QM/MM. Our investigation reveals a new N-halohistidyl intermediate in the catalytic cycle of vanadium chloroperoxidase (VCPO). This new intermediate, in turn, can explain the known inhibition of the enzyme by substrate under acidic conditions (pH$<$4). Additionally, we examine the possibility of replacing V in VCPO by Nb or Ta using QM modeling. We report the new result that the Gibbs free energy barriers of several steps of the catalytic cycle are lower in the case of artificial enzymes, incorporating NbO${}_4^{3-}$ or TaO${}_4^{3-}$ instead of VO${}_4^{3-}$. Our results suggest that these new artificial enzymes may catalyze the oxidation of halide faster than the natural enzyme.

We report a comprehensive investigation of the 5-androstene-3,17-dione to 4-androstene-3,17-dione isomerization in Ketosteroid Isomerase, gas phase and aqueous solution, applying as tools the Unified Reaction Valley Approach (URVA) and the Local Vibrational Mode Analysis. Conformational changes of the steroid rings are monitored via Cremer-Pople puckering coordinates. URVA identifies simultaneous breakage of the C${}_{\alpha }$–H bond and O–H bond formation with the catalytic acid, leading to an intermediate with the acid positioned over ring $A$ as the major chemical events of the first reaction step. Via a barrier-less shift, a second intermediate is formed with the acid being positioned over ring $B$. Then, according to URVA, breakage of the intermediate O–H bond, the formation of the new C${}_{\gamma }$–H bond accompanied by a double bond shift in rings $A$ and $B$ forms the major chemical events of the second reaction step, which is facilitated by favorable ring puckering. Reactions in protein and gas phase have comparable activation enthalpies, whereas the barrier in aqueous solution is higher, confirming that the major task of the enzyme pocket is to shield the migrating hydrogen atom and the catalyzing acid from interactions with solvent molecules diluting the catalytic power. We do not find exceptional H-bonding with Asp99 and Tyr14, excluding their catalytic activity. There is no strong hydrogen bonding in the TS, which could account for lowering the activation barrier. Our study provides a clear picture of the isomerization process, which will also inspire similar investigations of other important enzymatic reactions.

Protein secondary structure assignment, a subdiscipline of computational chemistry, is yet to be explored using deep learning techniques. Protein secondary structure elements are assigned to support structural analysis and prediction. Algorithms like DSSP, generally regarded as the gold standard for assigning the secondary structure of proteins, need full atom information to label protein coordinates. The PDB database has been the major repository for data on the 3D structures of proteins, nucleic acids, and other complex assemblies since 1971. However, a significant fraction of protein structures contains missing atoms. As a result, new approaches to reliably and consistently assigning secondary structures based on coarse-grained atomic coordinates are needed. While deep learning architectures have an unparalleled track record in applications such as protein structure prediction, there are only a few known deep learning solutions for structure assignment problems. While the gold standard methods are based on bonding information and other geometric characteristics, deep learning methods extract features themselves without human intervention. The benefit that standardised datasets provide to the effectiveness of deep learning systems in multiple domains motivated us to create a labeled dataset for protein structure assignment tasks. Additionally, a deep learning model, named PSSADL, solely based on $C_{\alpha }$ coordinates was trained on the generated dataset to validate its potency. The proposed method, which combines Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM)/Bidirectional LSTM networks, has been compared to the established standards and more recent techniques. The model achieved an accuracy of $\sim 96\%$ on the benchmark and individual test sets. The results show that deep learning techniques have a promising future in protein structure analysis, implying that the dataset developed as part of our work will be a valuable resource for further protein structure research.

Background: Most licensed antiviral drugs are nucleoside analogs. A recent research focuses on blocking a virus from entering the cells in the viral cell adsorption/entry stage. In this entry mechanism, the glycans present on the viral surface play a fundamental role. Homochiral L-peptides acting this fusion mechanism have shown some inhibition of viral infection. Peptides with regularly alternating enantiomeric sequence (L,D-peptides) can assume structures that are not accessible to the corresponding homochiral molecules. Furthermore, L,D-peptides are less sensitive to enzymatic digestion. Aim: In silico design of an L, D-peptide with a high affinity for the viral surface glycans and consequently able to interfere with its fusion mechanism. Methods: We used a $3\alpha ,6\alpha$-Mannopentaose (3-6MP) molecule to simulate a viral surface glycan. We performed molecular dynamics (MD) simulations of 3-6MP and D,L-peptide in water using the force field AMBER12-GLYCAM06i. We evaluated the binding constant from trajectories. The D,L-peptide molecule was modified over the sequence, the length, the terminals and finally glycosylated to attain a very high binding constant value for 3-6MP. In addition, we studied the specific interaction between T lymphocyte CD4 glycoprotein and HIV envelope glycoprotein gp120 through MD simulations between a D,L-peptide, bounded to a typical CD4 glycan, and a highly conserved HIV gp120 glycan. Results: Concerning the interaction with 3-6MP molecule, the very effective molecule obtained was H-d-Trp-l-Pro-d-Asn-l-Pro-d-Trp-l-Pro-d-Asn-l-Pro-OH where the Asn residues in position 3 and 7 are glycosylated with alpha-D-Mannopyranosyl-($1\to 3$)-[alpha-D-mannopyranosyl-($1\to 6$)]-alpha-D-mannopyranosyl-($1\to 4$)-N-acetyl-beta-D-glucopyranosyl-($1\to 4$)-N-acetyl-beta-D-glucopyranosyl-1-OH. As far as the interaction with HIV envelope is considered instead, the very effective molecule obtained, able to antagonize the CD4 glycoprotein, was H-d-Trp-l-Pro-d-Asn-l-Pro-d-Trp-l-Pro-d-Asn-l-Pro-OH where the Asn residue in position 3 is glycosylated with alpha-D-galactopyranosyl-($1\to 4$)- N-acetyl-beta-D-glucopyranosyl-($1\to 2$)-alpha-D-Mannopyranosyl-($1\to 3$)- [alpha-D-galactopyranosyl-($1\to 4$)- N-acetyl-beta-D-glucopyranosyl-($1\to 2$)- alpha-D-Mannopyranosyl-($1\to 6$)]- beta-D-mannopyranosyl-($1\to 4$)-N-acetyl-beta-D-glucopyranosyl-($1\to 4$)-N-acetyl-beta-D-glucopyranosyl-1-OH Conclusion: The above optimized glycosylated D,L-peptide molecules could be very promising representatives of a new powerful class of antiviral agents.

The indole nucleus offers a wide range of applications in medicinal chemistry, including anticancer activity. A series of novel indole chalcone derivatives containing benzyl-sulphonyl group were designed and in silico study was carried out against the thioredoxin system as an anticancer target. The drug-likeness properties of synthesized compounds were predicted. A study on the Passonline server predicts the compounds to have the least adverse reaction with thioredoxin inhibitor activity. As the designed compounds break not more than one ‘rule of five’, it can be concluded that these derivatives could be orally active. As per the ADMET analysis, except for C2 which contains para-substituted bromo, all the proposed compounds can be considered as safer lead molecules. According to the docking analysis, the derivatives showed a good binding affinity with the lowest minimum binding energy to the protein. According to the docking results, C3, C7, and C8 containing para chloro, para hydroxyl, and meta chloro groups, respectively, could be the powerful inhibitors among the derivatives. The molecules form hydrophobic and hydrogen bond interactions. C9 consisting of meta fluorine group may be a more potent thioredoxin inhibitor in comparison with Daucostero. Overall, the findings suggest that C3, C7, C8, and C9 compounds could be effective anticancer inhibitors of thioredoxin. The designed indole chalcones containing benzyl-sulfonyl group analogs could be safer and more or equivalent effective anticancer agents.

The dopamine (DA) metabolism changes are significant in Parkinson’s disease (PD). Levels of monoamine oxidases (MAOs) play a critical role in DA metabolism and oxidative damage. Increased levels of the MAO-B enzyme in the elderly raise oxidative damage and enhance neurodegenerative processes. Inhibiting MAO-B as an attractive target would be the best method for treating and understanding Parkinson’s disease. This study aimed to recognize a suitable inhibitor for the MAO-B enzyme using computational biology and compared it with Safinamide as a positive control. We used various computational biology techniques such as binding free energy, virtual screening, molecular dynamics (MD), and docking considerations to achieve the goal. To obtain a potent inhibitor, 41,852 compounds were taken from the Zinc database. After preparing compounds and the MAO-B enzyme, screening was performed using AutoDock Vina software. After screening, a potent natural inhibitor (ZINC00261335) was picked, and then, subsequent MD simulations for both ZINC00261335 and Safinamide were conducted via GROMACS software. The stability of the MAO-B_ZINC00261335 complex was excellent during the simulation, and the results of MM-PBSA analysis explicated that ZINC00261335 with ($-$118.353kJmol${}^{-1}$) is more potent than Safinamide ($-$89.305kJmol${}^{-1}$). Ultimately, the ADME study (lipophilicity, drug similarity and pharmacokinetic parameters) for ZINC00261335 was revealed, which is acceptable for human use. This study indicates that ZINC00261335 is a suitable MAO-B inhibitor and a great candidate for more laboratory studies.