Identification of Pak1 inhibitors using water thermodynamic analysis

Abstract

p21-activated kinases (Paks) play an integral component in various cellular diverse processes. The full activation of Pak is dependent upon several serine residues present in the N-terminal region, a threonine present at the activation loop, and finally the phosphorylation of these residues ensure the complete activation of Pak1. The present study deals with the identification of novel potent candidates of Pak1 using computational methods as anti-cancer compounds. A diverse energy based pharmacophore (e-pharmacophore) was developed using four co-crystal inhibitors of Pak1 having pharmacophore features of 5 (DRDRR), 6 (DRHADR), and 7 (RRARDRP and DRRDADH) hypotheses. These models were used for rigorous screening against e-molecule database. The obtained hits were filtered using ADME/T and molecular docking to identify the high affinity binders. These hits were subjected to hierarchical clustering using dendritic fingerprint inorder to identify structurally diverse molecules. The diverse hits were scored against generated water maps to obtain WM/MM ΔG binding energy. Furthermore, molecular dynamics simulation and density functional theory calculations were performed on the final hits to understand the stability of the complexes. Five structurally diverse novel Pak1 inhibitors (4835785, 32198676, 32407813, 76038049, and 32945545) were obtained from virtual screening, water thermodynamics and WM/MM ΔG binding energy. All hits revealed similar mode of binding pattern with the hinge region residues replacing the unstable water molecules in the binding site. The obtained novel hits could be used as a platform to design potent drugs that could be experimentally tested against cancer patients having increased Pak1 expression.     

Identification of abelson tyrosine kinase inhibitors as potential therapeutics for Alzheimer’s disease using multiple e-pharmacophore modeling and molecular dynamics

Efforts to combat Alzheimer’s disease are focused predominantly on inhibiting the activity of the enzyme(s) that have been identified to be responsible for the production of the amyloid-forming peptide. However, the inherent complexity associated with the network of pathways leading to the disease may involve additional targets for designing effective therapies. Recent experimental findings have identified abelson tyrosine kinase, a non-receptor kinase as a new target for Alzheimer’s. In this work, we employed energy optimized multiple pharmacophore modeling strategy from multiple c-Abl structures bound with ligands in the inactive ATP binding conformation (DFG-out). Virtual screening followed by docking of molecules from ChemBridge resulted in the identification of 10 best scoring molecules. MD simulations of the top three complexes revealed that Compound A, C are the most stable complexes with the most persistent protein–ligand interactions consistent with the calculated binding affinities for the top three compounds. Given the implied role of c-Abl not only in AD but in Parkinson’s disease, the identified compounds may serve as leads for effective neurotherapeutics.     

Inhibitor design against JNK1 through e-pharmacophore modeling docking and molecular dynamics simulations

c-Jun-NH2 terminal kinases (JNKs) come under a class of serine/threonine protein kinases and are encoded by three genes, namely JNK1, JNK2 and JNK3. Human JNK1 is a cytosolic kinase belonging to mitogen-activated protein kinase (MAPK) family, which plays a major role in intracrinal signal transduction cascade mechanism. Overexpressed human JNK1, a key kinase interacts with other kinases involved in the etiology of many cancers, such as skin cancer, liver cancer, breast cancer, brain tumors, leukemia, multiple myeloma and lymphoma. Thus, to unveil a novel human JNK1 antagonist, receptor-based pharmacophore modeling was performed with the available eighteen cocrystal structures of JNK1 in the protein data bank. Eighteen e-pharmacophores were generated from the 18 cocrystal structures. Four common e-pharmacophores were developed from the 18 e-pharmacophores, which were used as three-dimensional (3D) query for shape-based similarity screening against more than one million small molecules to generate a JNK1 ligand library. Rigid receptor docking (RRD) performed using GLIDE v6.3 for the 1683 compounds from in-house library and 18 cocrystal ligands with human JNK1 from lower stringency to higher stringency revealed 17 leads. Further to derive the best leads, dock complexes obtained from RRD were studied further with quantum-polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area (MM-GBSA). Four leads have showed lesser binding free energy and better binding affinity towards JNK1 compared to 18 cocrystal ligands. Additionally, JNK1–lead1 complex interaction stability was reasserted using 50?ns MD simulations run and also compared with the best resolute cocrystal structure using Desmond v3.8. Thus, the results obtained from RRD, QPLD, IFD and MD simulations indicated that lead1 might be used as a potent antagonist toward human JNK1 in cancer therapeutics.     

Multiple e-pharmacophore modelling pooled with high-throughput virtual screening,docking and molecular dynamics simulations to discover potential inhibitors of Plasmodium falciparum lactate dehydrogenase (PfLDH)

Development of new antimalarial drugs continues to be of huge importance because of the resistance of malarial parasite towards currently used drugs. Due to the reliance of parasite on glycolysis for energy generation, glycolytic enzymes have played important role as potential targets for the development of new drugs. Plasmodium falciparum lactate dehydrogenase (PfLDH) is a key enzyme for energy generation of malarial parasites and is considered to be a potential antimalarial target. Presently, there are nearly 15 crystal structures bound with inhibitors and substrate that are available in the protein data bank (PDB). In the present work, we attempted to consider multiple crystal structures with bound inhibitors showing affinity in the range of 1.4 × 10²–1.3 × 10⁶ nM efficacy and optimized the pharmacophore based on the energy involved in binding termed as e-pharmacophore mapping. A high throughput virtual screening (HTVS) combined with molecular docking, ADME predictions and molecular dynamics simulation led to the identification of 20 potential compounds which could be further developed as novel inhibitors for PfLDH.     

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling,structure based pharmacophore,molecular docking,and molecular dynamics simulations

MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.     

Identifying dual leucine zipper kinase (DLK) inhibitors using e-pharamacophore screening and molecular docking

Alzheimer’s is a neural disorder causing gradual loss in structure and function of nerve cell. To treat such disorders, c-Jun N-terminal Kinase (JNK) Pathway inhibitors were developed by representing chemical compounds that were used to inhibit the JNK signaling pathways. DLK is the stress sensor and implicating as regulatory factor in JNK pathway. Therefore, in the present investigation, pharmacophore screening was tried to identify the chemical compounds that involving inhibition of DLK proteins. To explore the pharmacophore region and mode of binding with DLK protein, N- (I H-pyrazol-3-y l) pyridin-2-aminer inhibitors were docked with DLK. Results reveal the information on the interaction mechanism of protein and ligand with chemical characteristics required to inhibit DLK protein. Such predicted information (AAAARH) was used as query to find out potential novel lead compounds sourced from public database. As an outcome of 65 compounds were listed based on the fitness score (2≥), and were subjected to glide HTVS.SP and XP. Best performing 5 lead compounds were shortlisted for dynamic simulations. This exhibited a constant RMSD over 20?ns of timescale.     

E-pharmacophore-based virtual screening to identify GSK-3β inhibitors

Glycogen synthase kinase-3β (GSK-3β) is a serine/threonine kinase which has attracted significant attention during recent years in drug design studies. The deregulation of GSK-3β increased the loss of hippocampal neurons by triggering apoptosis-mediating production of neurofibrillary tangles and alleviates memory deficits in Alzheimer’s disease (AD). Given its role in the formation of neurofibrillary tangles leading to AD, it has been a major therapeutic target for intervention in AD, hence was targeted in the present study. Twenty crystal structures were refined to generate pharmacophore models based on energy involvement in binding co-crystal ligands. Four common e-pharmacophore models were optimized from the 20 pharmacophore models. Shape-based screening of four e-pharmacophore models against nine established small molecule databases using Phase v3.9 had resulted in 1800 compounds having similar pharmacophore features. Rigid receptor docking (RRD) was performed for 1800 compounds and 20 co-crystal ligands with GSK-3β to generate dock complexes. Interactions of the best scoring lead obtained through RRD were further studied with quantum polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area. Comparing the obtained leads to 20 co-crystal ligands resulted in 18 leads among them, lead1 had the lowest docking score, lower binding free energy and better binding orientation toward GSK-3β. The 50?ns MD simulations run confirmed the stable nature of GSK-3β-lead1 docking complex. The results from RRD, QPLD, IFD and MD simulations confirmed that lead1 might be used as a potent antagonist for GSK-3β.     

Ligand-based and e-pharmacophore modeling, 3D-QSAR and hierarchical virtual screening to identify dual inhibitors of spleen tyrosine kinase (Syk) and janus kinase 3 (JAK3)

The clinical efficacy of multiple kinase inhibitors has caught the interest of Pharmaceutical and Biotech researchers to develop potential drugs with multi-kinase inhibitory activity for complex diseases. In the present work, we attempted to identify dual inhibitors of spleen tyrosine kinase (Syk) and janus kinase 3 (JAK3), keys players in immune signaling, by developing ideal pharmacophores integrating Ligand-based pharmacophore models (LBPMs) and Structure-based pharmacophore models (SBPMs), thereby projecting the optimum pharmacophoric required for inhibition of both the kinases. The four point LBPM; ADPR.14 suggested the presence of one hydrogen bond acceptor, one hydrogen bond donor, one positive ionizable, and one ring aromatic feature for Syk inhibitory activity and AADH.54 proposed the necessity of two hydrogen bond acceptor, one hydrogen bond donor, and one hydrophobic feature for JAK3 inhibitory activity. To our interest, SBPMs identified additional ring aromatic features required for inhibition of both the kinases. For Syk inhibitory activity, the hydrogen bond acceptor feature indicated by LBPM was devoid of forming hydrogen bonding interaction with the hinge region amino acid residue (Ala451). Thus merging the information revealed by both LBPMs and SBPMs, ideal pharmacophore models i.e. ADPRR.14 (Syk) and AADHR.54 (JAK3) were generated. These models after rigorous statistical validation were used for screening of Asinex database. The systematic virtual screening protocol, including pharmacophore and docking-based screening, ADME property, and MM-GBSA energy calculations, retrieved final 10 hits as dual inhibitors of Syk and JAK3. Final 10 hits thus obtained can aid in the development of potential therapeutic agents for autoimmune disorders. Also the top two hits were evaluated against both the enzymes.     

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.