Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.
Matched MeSH terms: Small Molecule Libraries/chemistry*
Transforming growth factor-β (TGF-β) is a member of a superfamily of pleiotropic proteins that regulate multiple cellular processes such as growth, development and differentiation. Following binding to type I and II TGF-β serine/threonine kinase receptors, TGF-β activates downstream signaling cascades involving both SMAD-dependent and -independent pathways. Aberrant TGF-β signaling is associated with a variety of diseases, such as fibrosis, cardiovascular disease and cancer. Hence, the TGF-β signaling pathway is recognized as a potential drug target. Various organic molecules have been designed and developed as TGF-β signaling pathway inhibitors and they function by either down-regulating the expression of TGF-β or by inhibiting the kinase activities of the TGF-β receptors. In this review, we discuss the current status of research regarding organic molecules as TGF-β inhibitors, focusing on the biological functions and the binding poses of compounds that are in the market or in the clinical or pre-clinical phases of development.
Matched MeSH terms: Small Molecule Libraries/chemistry
Due to the great biological importance of β-glucuronidase inhibitors, here in this study, we have synthesized a library of novel benzothiazole derivatives (1-30), characterized by different spectroscopic methods and evaluated for β-glucuronidase inhibitory potential. Among the series sixteen compounds i.e.1-6, 8, 9, 11, 14, 15, 20-23 and 26 showed outstanding inhibitory potential with IC50 value ranging in between 16.50 ± 0.26 and 59.45 ± 1.12 when compared with standard d-Saccharic acid 1,4-lactone (48.4 ± 1.25 µM). Except compound 8 and 23 all active analogs showed better potential than the standard. Structure activity relationship has been established.
Matched MeSH terms: Small Molecule Libraries/chemistry
γ-Secretase inhibitors (GSIs) and modulators (GSMs) are at the frontline of cancer and Alzheimer's disease research, respectively. While both are therapeutically promising, not much is known about their interactions with proteins other than γ-secretase. Signal peptide peptidase (SPP), like γ-secretase, is a multispan transmembrane aspartyl protease that catalyzes regulated intramembrane proteolysis. We used active site-directed photophore walking probes to study the effects of different GSIs and GSMs on the active sites of γ-secretase and SPP and found that nontransition state GSIs inhibit labeling of γ-secretase by activity-based probes but enhance labeling of SPP. The opposite is true of GSMs, which have little effect on the labeling of γ-secretase but diminish labeling of SPP. These results demonstrate that GSIs and GSMs are altering the structure of not only γ-secretase but also SPP, leading to potential changes in enzyme activity and specificity that may impact the clinical outcomes of these molecules.
Matched MeSH terms: Small Molecule Libraries/chemistry*
Nipah virus (NiV) infections are highly contagious and can cause severe febrile encephalitis. An outbreak of NiV infection has reported high mortality rates in Southeast Asian countries including Bangladesh, East Timor, Malaysia, Papua New Guinea, Vietnam, Cambodia, Indonesia, Madagascar, Philippines, Thailand and India. Considering the high risk for an epidemic outbreak, the World Health Organization (WHO) declared NiV as an emerging priority pathogen. However, there are no effective therapeutics or any FDA approved drugs available for the treatment of this infection. Among the known nine proteins of NiV, glycoprotein plays an important role in initiating the entry of viruses and attaching to the host cell receptors. Herein, three antiviral databases consisting of 79,892 chemical entities have been computationally screened against NiV glycoprotein (NiV-G). Particularly, multi-step molecular docking followed by extensive molecular binding interactions analyses, binding free energy estimation, in silico pharmacokinetics, synthetic accessibility and toxicity profile evaluations have been carried out for initial identification of potential NiV-G inhibitors. Further, molecular dynamics (MD) simulation has been performed to understand the dynamic properties of NiV-G protein-bound with proposed five inhibitors (G1-G5) and their interactions behavior, and any conformational changes in NiV-G protein during simulations. Moreover, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) based binding free energies (∆G) has been calculated from all MD simulation trajectories to understand the energy contribution of each proposed compound in maintaining and stabilizing the complex binding interactions with NiV-G protein. Proposed compounds showed high negative ∆G values ranging from -166.246 to -226.652 kJ/mol indicating a strong affinity towards the NiV-G protein.
Matched MeSH terms: Small Molecule Libraries/chemistry
Acquired paclitaxel (PTX) chemoresistance in triple-negative breast cancer (TNBC) can be inferred from the overexpression of toll-like receptor 4 (TLR4) and myeloid differentiation primary response 88 (MyD88) proteins and the activation of the TLR4/MyD88 cascading signalling pathway. Finding a new inhibitor that can attenuate the activation of this pathway is a novel strategy for reducing PTX chemoresistance. In this study, a series of small molecule compounds were synthesised and tested in combination with PTX against TNBC cells. The trimethoxy-substituted compound significantly decreased MyD88 overexpression and improved PTX activity in MDA-MB-231TLR4+ cells but not in HCCTLR4- cells. On the contrary, the trifluoromethyl-substituted compound with PTX synergistically improved the growth inhibition in both TNBC subtypes. The fluorescence titrations indicated that both compounds could bind with MD2 with good and comparable binding affinities. This was further supported by docking analysis, in which both compounds fit perfectly well and form some critical binding interactions with MD2, an essential lipid-binding accessory to TLR4 involved in activating the TLR-4/MyD88-dependent pathway.
Matched MeSH terms: Small Molecule Libraries/chemistry