Homology modeling, molecular dynamic simulation, and docking based binding site analysis of human dopamine (D4) receptor

Molecular recognition between volatile molecules and odorant binding proteins 7 by homology modeling, molecular docking and molecular dynamics simulation

BACKGROUND

Odorant-binding proteins (OBPs) in insects are key to detection and recognition of external chemical signals associated with survival. OBP7 in Spodoptera frugiperda's larval stage (SfruOBP7) may search for host plants by sensing plant volatiles, which are important sources of pest attractants and repellents. However, the atomic-level basis of binding modes remains elusive.

RESULTS

SfruOBP7 structure was constructed through homology modeling, and complex models of six plant volatiles ((E)-2-hexenol, α-pinene, (Z)-3-hexenyl acetate, lauric acid, O-cymene and 1-octanol) and SfruOBP7 were obtained through molecular docking. To study the detailed interactions between the six plant volatile molecules and SfruOBP7, we conducted three 300 ns molecular dynamics simulations for each study object. The correlation coefficients between binding free energy obtained by molecular mechanics/generalized Born surface area together with solvated interaction energy methods and experimental values are 0.90 and 0.88, respectively, showing a good correlation. By comparing binding free energy along with interaction patterns between SfruOBP7 and the six volatile molecules, hotspot residues of SfruOBP7 when binding with different volatile molecules were determined. Hydrophobic interactions stemming from van der Waals interactions play a significant role in SfruOBP7 and these plant volatile systems.

CONCLUSION

The optimized three-dimensional structure of SfruOBP7 and its binding modes with six plant volatiles revealed their interactions, thus providing a means for estimating the binding energies of other plant volatiles. Our study will help to guide the rational design of effective and selective insect attractants. © 2024 Society of Chemical Industry.

The Pivotal Distinction between Antagonists' and Agonists' Binding into Dopamine D4 Receptor-MD and FMO/PIEDA Studies

The dopamine D4 receptor (D4R) is a promising therapeutic target in widespread diseases, and the search for novel agonists and antagonists appears to be clinically relevant. The mechanism of binding to the receptor (R) for antagonists and agonists varies. In the present study, we conducted an in-depth computational study, teasing out key similarities and differences in binding modes, complex dynamics, and binding energies for D4R agonists and antagonists. The dynamic network method was applied to investigate the communication paths between the ligand (L) and G-protein binding site (GBS) of human D4R. Finally, the fragment molecular orbitals with pair interaction energy decomposition analysis (FMO/PIEDA) scheme was used to estimate the binding energies of L-R complexes. We found that a strong salt bridge with D3.32 initiates the inhibition of the dopamine D4 receptor. This interaction also occurs in the binding of agonists, but the change in the receptor conformation to the active state starts with interaction with cysteine C3.36. Such a mechanism may arise in the case of agonists unable to form a hydrogen bond with the serine S5.46, considered, so far, to be crucial in the activation of GPCRs. The energy calculations using the FMO/PIEDA method indicate that antagonists show higher residue occupancy of the receptor binding site than agonists, suggesting they could form relatively more stable complexes. Additionally, antagonists were characterized by repulsive interactions with S5.46 distinguishing them from agonists.

Combined approach of homology modeling, molecular dynamics, and docking: computer-aided drug discovery

With the continuous development in software, algorithms, and increase in computer speed, the field of computer-aided drug design has been witnessing reduction in the time and cost of the drug designing process. Structure based drug design (SBDD), which is based on the 3D structure of the enzyme, is helping in proposing novel inhibitors. Although a number of crystal structures are available in various repositories, there are various proteins whose experimental crystallization is difficult. In such cases, homology modeling, along with the combined application of MD and docking, helps in establishing a reliable 3D structure that can be used for SBDD. In this review, we have reported recent works, which have employed these three techniques for generating structures and further proposing novel inhibitors, for cytoplasmic proteins, membrane proteins, and metal containing proteins. Also, we have discussed these techniques in brief in terms of the theory involved and the various software employed. Hence, this review can give a brief idea about using these tools specifically for a particular problem.

Exploring the cause of the inhibitor 4AX attaching to binding site disrupting protein tyrosine phosphatase 4A1 trimerization by molecular dynamic simulation

Ectopic overexpression of protein tyrosine phosphatase of liver regeneration-1 (PTP4A1, also called PRL-1) markedly enhanced hepatocellular carcinoma (HCC) cells migration and invasion. The PTP4A1 trimerization played a vital role in mediating cell proliferation and motility. Biochemical and structural studies have proved that the compound 4AX, a well-known inhibitor for PRL1, directly binds to the PTP4A1 trimer interface and obstructs trimer formation of PTP4A1. However, the molecular basis of the ligand-4AX inhibition on PTP4A1 trimer conformations remains unclear. In this study, the docking analysis and the molecular dynamics simulation (MD simulation) study were performed to investigate how the molecule binding at each interface disrupted the trimer formation. The results suggested that the ligand-4AX attaching to the binding site changed the conformation of A:Q131, A:Q135 in the AC interface, C:R18, C:P96 in the CA interface and B:Q131 in the BA interface, leading to the weak interactions between subunits and thus resulting in the disruption of the PTP4A1 trimerization.

Conformational Transition of Key Structural Features Involved in Activation of ALK Induced by Two Neuroblastoma Mutations and ATP Binding: Insight from Accelerated Molecular Dynamics Simulations

Deregulated kinase activity of anaplastic lymphoma kinase (ALK) has been observed to be implicated in the development of tumor progression. The activation mechanism of ALK is proposed to be similar to other receptor tyrosine kinases (RTKs), but the distinct static X-ray crystal conformation of ALK suggests its unique conformational transition. Herein, we have illustrated the dynamic conformational property of wild-type ALK as well as the kinase activation equilibrium variation induced by two neuroblastoma mutations (R1275Q and Y1278S) and ATP binding by performing enhanced sampling accelerated Molecular Dynamics (aMD) simulations. The results suggest that the wild-type ALK is mostly favored in the inactive state, whereas the mutations and ATP binding promote a clear shift toward the active-like conformation. The R1275Q mutant stabilizes the active conformation by rigidifying the αC-in conformation. The Y1278S mutant promotes activation at the expense of a π-stacking hydrophobic cluster, which plays a critical role in the stabilization of the inactive conformation of native ALK. ATP produces a more compact active site and thereby facilitates the activation of ALK. Taken together, these findings not only elucidate the diverse conformations in different ALKs but can also shed light on new strategies for protein engineering and structural-based drug design for ALK.

Current Therapeutic Molecules and Targets in Neurodegenerative Diseases Based on in silico Drug Design

BACKGROUND

As the number of elderly persons increases, neurodegenerative diseases are becoming ubiquitous. There is currently a great need for knowledge concerning management of oldage neurodegenerative diseases; the most important of which are: Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis, and Huntington's disease.

OBJECTIVE

To summarize the potential of computationally predicted molecules and targets against neurodegenerative diseases.

METHOD

Review of literature published since 1997 against neurodegenerative diseases, utilizing as keywords: in silico, Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis ALS, and Huntington's disease was conducted.

RESULTS AND CONCLUSION

Due to the costs associated with experimentation and current ethical law, performing experiments directly on living organisms has become much more difficult. In this scenario, in silico techniques have been successful and have become powerful tools in the search to cure disease. Researchers use the Computer Aided Drug Design pipeline which: 1) generates 3- dimensional structures of target proteins through homology modeling 2) achieves stabilization through molecular dynamics simulation, and 3) exploits molecular docking through large compound libraries. Next generation sequencing is continually producing enormous amounts of raw sequence data while neuroimaging is producing a multitude of raw image data. To solve such pressing problems, these new tools and algorithms are required. This review elaborates precise in silico tools and techniques for drug targets, active molecules, and molecular docking studies, together with future prospects and challenges concerning possible breakthroughs in Alzheimer's, Parkinson's, Amyotrophic Lateral Sclerosis, and Huntington's disease.

Advantages of Structure-Based Drug Design Approaches in Neurological Disorders

OBJECTIVE

The purpose of the review is to portray the theoretical concept on neurological disorders from research data.

BACKGROUND

The freak changes in chemical response of nerve impulse causes neurological disorders. The research evidence of the effort done in the older history suggests that the biological drug targets and their effective feature with responsive drugs could be valuable in promoting the future development of health statistics structure for improved treatment for curing the nervous disorders.

METHODS

In this review, we summarized the most iterative theoretical concept of structure based drug design approaches in various neurological disorders to unfathomable understanding of reported information for future drug design and development.

RESULTS

On the premise of reported information we analyzed the model of theoretical drug designing process for understanding the mechanism and pathology of the neurological diseases which covers the development of potentially effective inhibitors against the biological drug targets. Finally, it also suggests the management and implementation of the current treatment in improving the human health system behaviors.

CONCLUSION

With the survey of reported information we concluded the development strategies of diagnosis and treatment against neurological diseases which leads to supportive progress in the drug discovery.

Exploring 3D structure of human gonadotropin hormone receptor at antagonist state using homology modeling, molecular dynamic simulation, and cross-docking studies

Human gonadotropin hormone receptor, a G-protein coupled receptor, is the target of many medications used in fertility disorders. Obtaining more structural information about the receptor could be useful in many studies related to drug design. In this study, the structure of human gonadotropin receptor was subjected to homology modeling studies and molecular dynamic simulation within a DPPC lipid bilayer for 100 ns. Several frames were thereafter extracted from simulation trajectories representing the receptor at different states. In order to find a proper model of the receptor at the antagonist state, all frames were subjected to cross-docking studies of some antagonists with known experimental values (Ki). Frame 194 revealed a reasonable correlation between docking calculated energy scores and experimental activity values (|r| = 0.91). The obtained correlation was validated by means of SSLR and showed the presence of no chance correlation for the obtained model. Different structural features reported for the receptor, such as two disulfide bridges and ionic lock between GLU90 and LYS 121 were also investigated in the final model.

Homology modeling, docking, and molecular dynamics simulation of the receptor GALR2 and its interactions with galanin and a positive allosteric modulator

Galanin receptor type 2 (GALR2) is a class A G-protein-coupled receptor (GPCR), and it has been reported that orthosteric ligands and positive allosteric modulators (PAMs) of GALR2 could potentially be used to treat epilepsy. So far, the X-ray structure of this receptor has not been resolved, and knowledge of the 3D structure of GALR2 may prove informative in attempts to design novel ligands and to explore the mechanism for the allosteric modulation of this receptor. In this study, homology modeling was used to obtain several GALR2 models using known templates. ProSA-web Z-scores and Ramachandran plots as well as pre-screening against a test dataset of known compounds were all utilized to select the best model of GALR2. Molecular dockings of galanin (a peptide) and a nonpeptide ligand were carried out to choose the (GALR2 model)-galanin complex that showed the closest agreement with the corresponding experimental data. Finally, a 50-ns MD simulation was performed to study the interactions between the GALR2 model and the synthetic and endogenous ligands. The results from docking and MD simulation showed that, besides the reported residues, Tyr160(4.60), Ile105(3.32), Ala274(7.35), and Tyr163(ECL2) also appear to play important roles in the binding of galanin. The potential allosteric binding pockets in the GALR2 model were then investigated via MD simulation. The results indicated that the mechanism for the allosteric modulation caused by PAMs is the binding of the PAM at pocket III, which is formed by galanin, ECL2, TM2, TM3, and ECL1; this results in the disruption of the Na(+)-binding site and/or the Na(+) ion pathway, leading to GALR2 agonism.