Novel Molecular Targets of Antidepressants

Antidepressants target a variety of proteins in the central nervous system (CNS), the most important belonging to the family of G-protein coupled receptors and the family of neurotransmitter transporters. The increasing number of crystallographic structures of these proteins have significantly contributed to the knowledge of their mechanism of action, as well as to the design of new drugs. Several computational approaches such as molecular docking, molecular dynamics, and virtual screening are useful for elucidating the mechanism of drug action and are important for drug design. This review is a survey of molecular targets for antidepressants in the CNS and computer based strategies to discover novel compounds with antidepressant activity.

The Compound (E)-2-cyano-N,3-diphenylacrylamide (JMPR-01): A Potential Drug for Treatment of Inflammatory Diseases

The compound (E)-2-cyano-N,3-diphenylacrylamide (JMPR-01) was structurally developed using bioisosteric modifications of a hybrid prototype as formed from fragments of indomethacin and paracetamol. Initially, in vitro assays were performed to determine cell viability (in macrophage cultures), and its ability to modulate the synthesis of nitrite and cytokines (IL-1β and TNFα) in non-cytotoxic concentrations. In vivo, anti-inflammatory activity was explored using the CFA-induced paw edema and zymosan-induced peritonitis models. To investigate possible molecular targets, molecular docking was performed with the following crystallographic structures: LT-A4-H, PDE4B, COX-2, 5-LOX, and iNOS. As results, we observed a significant reduction in the production of nitrite and IL-1β at all concentrations used, and also for TNFα with JMPR-01 at 50 and 25 μM. The anti-edematogenic activity of JMPR-01 (100 mg/kg) was significant, reducing edema at 2–6 h, similar to the dexamethasone control. In induced peritonitis, JMPR-01 reduced leukocyte migration by 61.8, 68.5, and 90.5% at respective doses of 5, 10, and 50 mg/kg. In silico, JMPR-01 presented satisfactory coupling; mainly with LT-A4-H, PDE4B, and iNOS. These preliminary results demonstrate the strong potential of JMPR-01 to become a drug for the treatment of inflammatory diseases.

On the Critical Resolved Shear Stress and its Importance in the Fatigue Performance of Steels and other Metals with Different Crystallographic Structures

This study deals with the numerical estimation of the fatigue life represented in the form of strength-life (S-N, or Wöhler) curves of metals with different crystallographic structures, namely body-centered cubic (BCC) and face-centered cubic (FCC). Their life curves are determined by analyzing the initiation of a short crack under the influence of microstructure and subsequent growth of the long crack, respectively. Micro-models containing microstructures of the materials are set up by using the finite element method (FEM) and are applied in combination with the Tanaka-Mura (TM) equation in order to estimate the number of cycles required for the crack initiation. The long crack growth analysis is conducted using the Paris law. The study shows that the crystallographic structure is not the predominant factor that determines the shape and position of the fatigue life curve in the S-N diagram, but it is rather the material parameter known as the critical resolved shear stress (CRSS). Even though it is an FCC material, the investigated austenitic stainless steel AISI 304 shows an untypically high fatigue limit (208 MPa), which is higher than the fatigue limit of the BCC vanadium-based micro-alloyed forging steel AISI 1141 (152 MPa).

Activity Cliffs As Protein-Related Phenomenon: Investigation Using Machine Learning Against Numerous Protein Kinases

Activity cliffs (ACs) are analogous compounds of significant affinity discrepancies against certain biotarget. We propose that the ACs phenomenon is protein-related and that the propensity of certain target to have ACs can be predicted by some intrinsic protein properties. We pursued this assumption by collecting the crystallographic structures of 84 protein kinases, each of which has numerous reported inhibitors (hundreds). Following data augmentation using synthetic minority oversampling technique (SMOTE), we attempted to correlate the presence/absence of ACs within the ligand pools of collected protein kinases with their corresponding protein properties using genetic algorithm (GA) coupled with variety of machine learners (MLs). Very good GA-ML models were achieved with accuracies of around 75% against external testing set. The models were further validated by Y-scrambling. Shapely additive explanations highlighted the significance of protein rotatable bonds, hydrophobic and acidic residues in relation to the presence of ACs. These results support the hypothesis that ACs are protein-related.

DATABASE ENRICHMENTS OF MAO-B THROUGH ENSEMBLE DOCKING

Objective: The recent growth of highly resoluted crystallographic structures, together with the continuous improvements of the computing power, has established molecular docking as a leading drug design technique. However, the problems concerning the receptor flexibility and the lowered ability of docking software to correctly score the occurred interactions in some receptors are still relevant. Methods: Recently, several research groups have reported an enhancement in enrichment values when ensemble docking has been applied. Therefore, we utilized the latest technique for a dataset of Monoamine Oxidase–B (MAO-B) inhibitors. The docking program GOLD 5.3 was used in our study. Several docking parameters (grid space, scoring functions and ligand flexibility) were altered in order to achieve the optimal docking protocol. Results: The results of 200 000+docking simulations are represented in a modest table. The ensembled simulations demonstrated low ability of the docking software to correctly score the actives seeded in the dataset. However, the superimposed complex-1S3B-1OJA-1OJC, achieved a moderate enrichment value equaled to 9. No significant improvements were noted when five complexed receptors were employed. Conclusion: As a conclusion, it should be noted that in some cases the ensemble docking enhanced the database enrichments, however overall the value is not suitable for future virtual screening. Further investigations in that area should be considered.

Structures of the Plasmodium falciparum heat-shock protein 70-x ATPase domain in complex with chemical fragments identify conserved and unique binding sites

Plasmodium falciparum invades erythrocytes and extensively modifies them in a manner that increases the virulence of this malaria parasite. A single heat-shock 70 kDa-type chaperone, PfHsp70-x, is among the parasite proteins exported to the host cell. PfHsp70-x assists in the formation of a key protein complex that underpins parasite virulence and supports parasite growth during febrile episodes. Previous work resolved the crystallographic structures of the PfHsp70-x ATPase and substrate-binding domains, and showed them to be highly similar to those of their human counterparts. Here, 233 chemical fragments were screened for binding to the PfHsp70-x ATPase domain, resulting in three crystallographic structures of this domain in complex with ligands. Two binding sites were identified, with most ligands binding proximal to the ATPase nucleotide-binding pocket. Although amino acids participating in direct ligand interactions are conserved between the parasite and human erythrocytic chaperones, one nonconserved residue is also present near the ligand. This work suggests that PfHsp70-x features binding sites that may be exploitable by small-molecule ligands towards the specific inhibition of the parasite chaperone.

On Computation and Analysis of Entropy Measures for Crystal Structures

In recent years, the study of topological indices associated to different molecular tubes and structures gained a lot of attention of the researchers—working in Chemistry and Mathematics. These descriptors play an important role in describing different properties associated to the objects of study. Moreover, Shannon’s entropy concept—a slightly different but more effective approach—provides structural information related to the molecular graphs. In this article, we have computed and analyzed different entropy measures associated to different crystallographic structures. In particular, we have worked on the Zagreb entropies, hyper and augmented Zagreb entropies, and forgotten and Balaban entropies for the crystallographic structures of the cuprite Cu 2 O and titanium difluoride TiF 2 .

The Serological Cross-Detection of Bat-Borne Hantaviruses: A Valid Strategy or Taking Chances?

Bats are hosts of a range of viruses, and their great diversity and unique characteristics that distinguish them from all other mammals have been related to the maintenance, evolution, and dissemination of these pathogens. Recently, very divergent hantaviruses have been discovered in distinct species of bats worldwide, but their association with human disease remains unclear. Considering the low success rates of detecting hantavirus RNA in bat tissues and that to date no hantaviruses have been isolated from bat samples, immunodiagnostic tools could be very helpful to understand pathogenesis, epidemiology, and geographic range of bat-borne hantaviruses. In this sense, we aimed to identify in silico immunogenic B-cell epitopes present on bat-borne hantaviruses nucleoprotein (NP) and verify if they are conserved among them and other selected members of Mammantavirinae, using a combination of (the three most used) different prediction algorithms, ELLIPRO, Discotope 2.0, and PEPITO server. To support our data, we in silico modeled 3D structures of NPs from representative members of bat-borne hantaviruses, using comparative and ab initio methods due to the absence of crystallographic structures of studied proteins or similar models in the Protein Data Bank. Our analysis demonstrated the antigenic complexity of the bat-borne hantaviruses group, showing a low sequence conservation of epitopes among members of its own group and a minor conservation degree in comparison to Orthohantavirus, with a recognized importance to public health. Our data suggest that the use of recombinant rodent-borne hantavirus NPs to cross-detect antibodies against bat- or shrew-borne viruses could underestimate the real impact of this virus in nature.

On Ve-Degree-Based Irregularity Properties of the Crystallographic Structure of Molecules

Irregularity indices are usually used for quantitative characterization of the topological structure of nonregular graphs. In numerous applications and problems in material engineering and chemistry, it is useful to be aware that how irregular a molecular structure is? In this paper, we are interested in formulating closed forms of irregularity measures of some of the crystallographic structures of Cu 2 O p , q , r and crystallographic structure of titanium difluoride of T i F 2 p , q , r . These theoretical conclusions provide practical guiding significance for pharmaceutical engineering and complex network and quantify the degree of folding of long organic molecules.

Unraveling the unbinding pathways of SARS-CoV-2 Papain-like proteinase known inhibitors by Supervised Molecular Dynamics simulation

The COVID-19 disease has infected and killed countless people all over the world since its emergence at the end of 2019. No specific therapy for COVID-19 is not currently available, and urgent treatment solutions are needed. Recent studies have found several potential molecular targets, and one of the most critical proteins of the SARS-CoV-2 virus work machine is the Papain-like protease (Plpro). Potential inhibitors are available, and their X-ray crystallographic structures in complex with this enzyme have been determined recently. However, their activities against this enzyme are insufficient and need to be characterized and improved to be of clinical values. Therefore, in this work, by utilizing the Supervised Molecular Dynamics (SuMD) simulation method, we achieved multiple unbinding events of Plpro inhibitors, GRL0617, and its derivates, and captured and understood the details of the unbinding pathway. We found that residues of the BL2 loop, such as Tyr268 and Gln269, play major roles in the unbinding pathways, but the most important contributing factor is the natural movements and behavior of the BL2 loop, which can control the entire process. We believe that the details found in this study can be used to refine and optimize potential inhibitors like GRL0617 and design more efficacious inhibitors as a treatment for the SARS-CoV-2 virus.