E-pharmacophore filtering and molecular dynamics simulation studies in the discovery of potent drug-like molecules for chronic kidney disease

Pharmacoinformatics approach for type 2 diabetes mellitus therapeutics using phytocompounds from Costus genus: an in-silico investigation

Type 2 Diabetes Mellitus (T2DM), as a significant health concern globally, particularly in India, underscoring the vital need for effective therapeutics. Current drug therapies for T2DM may have limitations, leading researchers to explore natural products as alternatives. In this study. We have investigated the anti-diabetic compounds from the Costus genus, known as the insulin plant, which is abundant in southern India. The bioinformatics tools and software used for in-silico analysis to identify potential therapeutic compounds and hub genes associated with T2DM in the Indian population that could cut short the in-vitro and in-vivo experimental approaches in near future. The systematic review and combinatorial in-silico analysis revealed IGF2BP2, INS and TCF as the key targets that are associated with T2DM. The compounds stigmasterol, cycloartenol, and diosgenone were explored to be potent among all the 38 phytocompounds from genus Costus with binding energies -8.48, -10.07, and -10.31 kcal/mol against IGF2BP2, INS and TCF. The molecular dynamics (MD) simulation studies of these complexes demonstrated stable and consistent dynamic behavior, particularly in the INS-cycloartenol, IGF2BP2-stigmasterol and TCF7L2-diosgenone complexes. The identified compounds and associated targets represent potential candidates for T2DM therapeutics in the Indian population. The pharmacoinformatics approach presented in the study could streamline the drug discovery process by prioritizing compounds for further experimental validation.Communicated by Ramaswamy H. Sarma.

The identification of c-Abl inhibitors as potential agents for Parkinson's disease: a preliminary in silico approach

Parkinson's disease (PD) is the most common movement disorder worldwide. PD is primarily associated with the mutation, overexpression, and phosphorylation of α-synuclein. At the molecular level, the upstream protein c-Abl, a tyrosine kinase, has been shown to regulate α-synuclein activation and expression patterns. This study aimed to identify potential c-Abl inhibitors through in silico approaches. Molecular docking was performed using PyRx software, followed by Prime MM-GBSA studies. BBB permeability and toxicity were predicted using CBligand and ProTox-II, respectively. ADME was assessed using QikProp. Molecular dynamics were carried out using Desmond (Academic version). DFT calculations were performed using the Gaussian 16 suite program. The binding scores of the top hits, norimatinib, DB07326, and entinostat were - 11.8 kcal/mol, - 11.8 kcal/mol, and - 10.8 kcal/mol, respectively. These hits displayed drug-likeness with acceptable ADME properties, except for the standard, nilotinib, which violated Lipinski's rule of five. Similarly, the molecular dynamics showed that the top hits remained stable during the 100 ns simulation. DFT results indicate DB04739 as a potent reactive hit. While based on toxicity prediction, entinostat may be a potential candidate for preclinical and clinical testing in PD. Further studies are warranted to confirm the activity and efficacy of these ligands for PD.

Identification of BACE-1 Inhibitors against Alzheimer’s Disease through E-Pharmacophore-Based Virtual Screening and Molecular Dynamics Simulation Studies: An Insilco Approach

Alzheimer is a severe memory and cognitive impairment neurodegenerative disease that is the most common cause of dementia worldwide and characterized by the pathological accumulation of tau protein and amyloid-beta peptides. In this study, we have developed E-pharmacophore modeling to screen the eMolecules database with the help of a reported co-crystal structure bound with Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1 (BACE-1). Flumemetamol, florbetaben, and florbetapir are currently approved drugs for use in the clinical diagnosis of Alzheimer’s disease. Despite the benefits of commercially approved drugs, there is still a need for novel diagnostic agents with enhanced physicochemical and pharmacokinetic properties compared to those currently used in clinical practice and research. In the E-pharmacophore modeling results, it is revealed that two aromatic rings (R19, R20), one donor (D12), and one acceptor (A8) are obtained, and also that similar pharmacophoric features of compounds are identified from pharmacophore-based virtual screening. The identified screened hits were filtered for further analyses using structure-based virtual screening and MM/GBSA. From the analyses, top hits such as ZINC39592220 and en1003sfl.46293 are selected based on their top docking scores (−8.182 and −7.184 Kcal/mol, respectively) and binding free energy (−58.803 and −56.951 Kcal/mol, respectively). Furthermore, a molecular dynamics simulation and MMPBSA study were performed, which revealed admirable stability and good binding free energy throughout the simulation period. Moreover, Qikprop results revealed that the selected, screened hits have good drug-likeness and pharmacokinetic properties. The screened hits ZINC39592220 and en1003sfl.46293 could be used to develop drug molecules against Alzheimer’s disease.

Structural exploration of common pharmacophore based berberine derivatives as novel histone deacetylase inhibitor targeting HDACs enzymes

Histone deacetylase (HDAC) inhibitors, are new class of cancer chemotherapeutics used in clinical development. It plays a pivotal role in restoring the acetylation balance and lysine residual deacetylation in histone and non-histone proteins. Notably, HDAC inhibitors have been approved by FDA to treat different malignancies. Recently, we demonstrated berberine as pan inhibitor for HDAC. However, isoform specific inhibition of HDAC enzyme is highly warranted. Therefore, a pharmacophore based structural exploration of berberine is in need to be developed, berberine is composed of four portions namely: a) zinc binding group (ZBG), b) Linker (scaffold), c) connect unit (CU), and d) surface recognition moiety (SRM). We derived four berberine derivatives based on common HDAC inhibition pharmacophore, compound 4 possesses highest bit score by molecular docking and compound stability by HOMOs-LUMOs analysis. It is concluded that, structurally modified berberine derivatives shown better inhibition of HDAC enzymes offering improved clinical efficacy.

Structural and functional insights on vitamin D receptor and CYP24A1 deleterious single nucleotide polymorphisms: A computational and pharmacogenomics perpetual approach

The development of chronic kidney disease (CKD) drugs remains a challenge due to the variations in the genes. The vitamin D receptor (VDR) and Cytochrome 24A1 (CYP24A1) genetic variants might affect the drug potency, efficacy and pathway. Here we have to analyse and determine the deleterious single-nucleotide polymorphisms (nsSNPs) of VDR and CYP24A1 genes and their different population's drug responses in different populations to understand the key role in CKD. Among that the large scale of nsSNP, we used certain computational tools that predicted six missense variants are observed to be significantly damaging effect and SNP variability with large differences in various populations. Molecular docking studies were carried out by clinical and our screened compounds to VDR and CYP24A1. Docking results revealed all the compounds have a good binding affinity (Score). The screened compounds (TCM_2868 and UNPD_141613) show good binding affinity when compared to known compounds. The QM/MM study revealed that the compounds have electron transfer ability and act as a donor/acceptor to mutated proteins. The structural and conformational changes of protein complexes were analysed by molecular dynamics study. Hence, this study helps to identify suitable drugs through drug discovery in CKD treatment. The abovementioned compounds have more binding affinity, efficacy, and potency of both wild and mutant of VDR and CYP24A1.

Discovery of human autophagy initiation kinase ULK1 inhibitors by multi-directional in silico screening strategies

Autophagy is a self-catabolic mechanism employed by cancer cells to acquire nutrients and energy in times of stress conditions, thereby leading to its progression and survival. Thus, autophagy inhibition has emerged as a new paradigm in the area of cancer treatment. Here, we leverage multi-dimensional screening campaigns aim to identify potent inhibitors against an early and an essential autophagic kinase, ULK1 from DrugBank database. In particular, receptor-based hypothesis, pharmacophore hypothesis, e-pharmacophore hypothesis and shape similarity-based screening algorithm were employed. Of note, the results of the different algorithm were then integrated to eliminate the false positive prediction. Moreover, the inhibitory activities and PK/PD parameters of the leads were tested by Glide and Qikprop algorithm. This resulted in a set of four hits namely; DB12686, DB08341, DB07936, and DB07163. Finally, molecular dynamics simulation was performed using the GROMACS package, to validate the binding kinetics of the hit compound. The compound activity in vitro was assessed by PASS algorithm, highlights the anti-cancer activities of the hits. The structural insights reveal existence of functional moieties such as piperidine carboxamide, benzenesulfonamide, benzamide, and isoindolone in the resultant hits which plays a major role in the anti-cancer activity. Overall, we strongly believe that these ULK1 antagonists could be novel and potent drug candidates for future cancer therapeutics.

In silico identification and screening of CYP24A1 inhibitors: 3D QSAR pharmacophore mapping and molecular dynamics analysis

Vitamin D is a key signalling molecule that plays a vital role in the regulation of calcium phosphate homeostasis and bone remodelling. The circulating biologically active form of vitamin D is regulated by the catabolic mechanism of cytochrome P450 24-hydroxylase (CYP24A1) enzyme. The over-expression of CYP24A1 negatively regulates the vitamin D level, which is the causative agent of chronic kidney disease, osteoporosis and several types of cancers. In this study, we found three potential lead molecules adverse to CYP24A1 through structure-based, atom-based pharmacophore and e-pharmacophore-based screening methods. Analysis was done by bioinformatics methods and tools like binding affinity (binding free energy), chemical reactivity (DFT studies) and molecular dynamics simulation (protein-ligand stability). Combined computational investigation showed that the compounds NCI_95001, NCI_382818 and UNPD_141613 may have inhibitory effects against the CYP24A1 protein.

Recent Developments and Applications of the MMPBSA Method

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.

Insight into binding mechanisms of inhibitors MKP56, MKP73, MKP86, and MKP97 to HIV-1 protease by using molecular dynamics simulation

HIV-1 protease (PR) has been a significant target for design of potent inhibitors curing acquired immunodeficiency syndrome. Molecular dynamics simulations coupled with molecular mechanics Poisson-Boltzmann surface area method were performed to study interaction modes of four inhibitors MKP56, MKP73, MKP86, and MKP97 with PR. The results suggest that the main force controlling interactions of inhibitors with PR should be contributed by van der Waals interactions between inhibitors and PR. The cross-correlation analyses based on MD trajectories show that inhibitor binding produces significant effect on the flap dynamics of PR. Hydrogen bond analyses indicate that inhibitors can form stable hydrogen bonding interactions with the residues from the catalytic strands of PR. The contributions of separate residues to inhibitor bindings are evaluated by using residue-based free energy decomposition method and the results demonstrate that the CH-π and CH-CH interactions between the hydrophobic groups of inhibitors with residues drive the associations of inhibitors with PR. We expect that this study can provide a significant theoretical aid for design of potent inhibitors targeting PR.