Pharmacophore Modelling and 3D-QSAR Studies on N(3)-Phenylpyrazinones as Corticotropin-Releasing Factor 1 Receptor Antagonists

Discovery of novel pyrrolo[2,3-d]pyrimidine derivatives as anticancer agents: virtual screening and molecular dynamic studies

CDK/Cyclins are dysregulated in several human cancers. Recent studies showed inhibition of CDK4/6 was responsible for controlling cell cycle progression and cancer cell growth. In the present study, atom-based and field-based 3D-QSAR, virtual screening, molecular docking and molecular dynamics studies were done for the development of novel pyrrolo[2,3-d]pyrimidine (P2P) derivatives as anticancer agents. The developed models showed good Q2 and r2 values for atom-based 3D-QSAR, which were equal to 0.7327 and 0.8939, whereas for field-based 3D-QSAR the values were 0.8552 and 0.6255, respectively. Molecular docking study showed good-binding interactions with amino acid residues such as VAL-101, HIE-100, ASP-104, ILE-19, LYS-147 and GLU-99, important for CDK4/6 inhibitory activity by using PDB ID: 5L2S. Pharmacophore hypothesis (HHHRR_1) was used in the screening of ZINC database. The top scored ZINC compound ZINC91325512 showed binding interactions with amino acid residues VAL-101, ILE-19, and LYS-147. Enumeration study revealed that the screened compound R1 showed binding interactions with VAL 101 and GLN 149 residues. Furthermore, the Molecular dynamic study showed compound R1, ZINC91325512 and ZINC04000264 having RMSD values of 1.649, 1.733 and 1.610 Å, respectively. These ZINC and enumerated compounds may be used for the development of novel pyrrolo[2,3-d]pyrimidine derivatives as anticancer agent.

The Current Perspectives in Clinical Research: Computer-Assisted Drug Designing, Ethics, and Good Clinical Practice

In the era of emerging microbial and non-communicable diseases and re-emerging microbial infections, the medical fraternity and the public are plagued by under-preparedness. It is evident by the severity of the Coronavirus disease (COVID-19) pandemic that novel microbial diseases are a challenge and are challenging to control. This is mainly attributed to the lack of complete knowledge of the novel microbe’s biology and pathogenesis and the unavailability of therapeutic drugs and vaccines to treat and control the disease. Clinical research is the only answer utilizing which can handle most of these circumstances. In this review, we highlight the importance of computer-assisted drug designing (CADD) and the aspects of molecular docking, molecular superimposition, 3D-pharmacophore technology, ethics, and good clinical practice (GCP) for the development of therapeutic drugs, devices, and vaccines.

Integrated computational approach for in silico design of new purinyl pyridine derivatives as B-Raf kinase inhibitors

B-Raf is one among the most frequently mutating proto-oncogene which is associated with the serine/threonine Raf kinase family involved in the RAS-RAF-MEK-ERK pathway, which is the most deregulated pathway in human cancers. Mutant B-Raf ^V600E got an excellent scope for investigation in cancer as a potential therapeutic target. Formerly B-Raf^V600E is considered the molecular target for numerous antitumor compounds like purinyl pyridine and pyrimidine derivatives. In the current research work using molecular docking approach of Schrodinger Glide 5.6 version, ligand docking, pharmacophore-based virtual screening, binding free energy calculations of a series of 2-amino purinyl pyridine and pyrimidine derivatives were modeled, their docking values were predicted, that were considered to be potent against B-Raf ^V600E. A five-point hypothesis accompanied by a hydrogen bond acceptor(A), two hydrogen bond donors(D), and two aromatic rings (R) was built with a justifiable R² value of 0.91 and a Q² value of 0.64. Then by using Asinex Elite Synergy database, virtual screening was performed, and identified several potential hits. Subsequently, the molecules which had interactions with the target B-Raf kinase were determined by subjecting the obtained hits for SP and XP docking processes. Finally, for the top leads obtained, binding free energies were accomplished. About 16 new purinyl pyridine molecules were also designed. Almost nine molecules manifested crucial ligand interactions and binding free energies. At the outset, this research paved the way for us in spotting new molecules with B-Raf inhibitory activity, which can further be explored to design molecules with enhanced pharmacokinetic profiles.

Antimicrobial cell penetrating peptides with bacterial cell specificity: pharmacophore modelling, quantitative structure activity relationship and molecular dynamics simulation

Current research has shown cell-penetrating peptides and antimicrobial peptides (AMPs) as probable vectors for use in drug delivery and as novel antibiotics. It has been reported that the higher the therapeutic index (TI) the higher would be the bacterial cell penetrating ability. To the best of our knowledge, no in-silico study has been performed to determine bacterial cell specificity of the antimicrobial cell penetrating peptides (aCPP's) based on their TI. The aim of this study was to develop a quantitative structure activity relationship (QSAR) model, which can estimate antimicrobial potential and cell-penetrating ability of aCPPs against S. aureus, to confirm the relationship between the TI and aCPPs and to identify specific descriptors responsible for aCPPs penetrating ability. Molecular dynamics (MD) simulation was also performed to confirm the membrane insertion of the most active aCPPs obtained from the QSAR study. The most appropriate pharmacophore was identified to predict the aCPP's activity. The statistical results confirmed the validity of the model. The QSAR model was successful in identifying the optimal aCPP with high activity prediction and provided insights into the structural requirements to correlate their TI to cell penetrating ability. MD simulation of the best aCPP with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer confirmed its interaction with the membrane and the C-terminal residues of the aCPP played a key role in membrane penetration. The strategy of combining QSAR and molecular dynamics, allowed for optimal estimation of ligand-target interaction and confirmed the importance of Trp and Lys in interacting with the POPC bilayer. Communicated by Ramaswamy H. Sarma.

Pharmacophore modeling, atom based 3D-QSAR and Molecular docking approaches to screen C-X-C chemokine receptor type 4 antagonists as microbicides for human immunodeficiency virus-1

The C-X-C chemokine receptor type 4 receptor CXCR4 which acts as a co-receptor for human immunodeficiency virus-1, expressed in the later stages of infection is considered as an attractive and new target for drug design. Microbicides acting as co-receptor blockers are highly significant as these drugs block HIV lifecycle at early stage itself. The urgent need for a safe and effective microbicide urges to explore new CXCR4 antagonists which could be developed as microbicides. The pharmacophore based 3D-QSAR models and docking models were developed using PHASE and GLIDE modules of Schrodinger software. Three-dimensional quantitative structure-activity relationships (3D-QSAR) studies and pharmacophore modelling was carried out on a dataset of 114 CXCR4 antagonists with the intention of exploring entry inhibitors with better therapeutic potential. A training set of 43 compounds was used to create 3D-QSAR models and they were validated using a test set of 28 compounds. CXCR4 antagonists with good inhibitory activity could be designed and structurally modified based upon the QSAR model developed with necessary pharmacophore features. The results revealed that the common pharmacophore hypothesis ADHPR.1 was used for 3D-QSAR model development and the most active compound, CXCR4 antagonist no.44 which is a imidazopyridine-tetrahydro-8-quinolinamine derivative interacted with the CXCR4 receptor residue ASP 97 by the formation of a hydrogen bond. Also, the docking studies were carried out for the dataset for analyzing the binding conformation of CXCR4 and 114 antagonists. The results obtained from the 3D-QSAR studies and docking simulation can be used for designing new and potent CXCR4 antagonists. The compound identified from this study can be taken up further for validation by in vitro/in vivo studies.

Mechanistic Insights into the Binding of Class IIa HDAC Inhibitors toward Spinocerebellar Ataxia Type-2: A 3D-QSAR and Pharmacophore Modeling Approach

Spinocerebellar ataxia (SCA-2) type-2 is a rare neurological disorder among the nine polyglutamine disorders, mainly caused by polyQ (CAG) trinucleotide repeats expansion within gene coding ataxin-2 protein. The expanded trinucleotide repeats within the ataxin-2 protein sequesters transcriptional cofactors i.e., CREB-binding protein (CBP), Ataxin-2 binding protein 1 (A2BP1) leading to a state of hypo-acetylation and transcriptional repression. Histone de-acetylases inhibitors (HDACi) have been reported to restore transcriptional balance through inhibition of class IIa HDAC's, that leads to an increased acetylation and transcription as demonstrated through in-vivo studies on mouse models of Huntington's. In this study, 61 di-aryl cyclo-propanehydroxamic acid derivatives were used for developing three dimensional (3D) QSAR and pharmacophore models. These models were then employed for screening and selection of anti-ataxia compounds. The chosen QSAR model was observed to be statistically robust with correlation coefficient (r²) value of 0.6774, cross-validated correlation coefficient (q²) of 0.6157 and co-relation coefficient for external test set (pred_r²) of 0.7570. A high F-test value of 77.7093 signified the robustness of the model. Two potential drug leads ZINC 00608101 (SEI) and ZINC 00329110 (ACI) were selected after a coalesce procedure of pharmacophore based screening using the pharmacophore model ADDRR.20 and structural analysis using molecular docking and dynamics simulations. The pharmacophore and the 3D-QSAR model generated were further validated for their screening and prediction ability using the enrichment factor (EF), goodness of hit (GH), and receiver operating characteristics (ROC) curve analysis. The compounds SEI and ACI exhibited a docking score of −10.097 and −9.182 kcal/mol, respectively. An evaluation of binding conformation of ligand-bound protein complexes was performed with MD simulations for a time period of 30 ns along with free energy binding calculations using the g_mmpbsa technique. Prediction of inhibitory activities of the two lead compounds SEI (7.53) and ACI (6.84) using the 3D-QSAR model reaffirmed their inhibitory characteristics as potential anti-ataxia compounds.