Recent improvements to the free energy perturbation (FEP) calculations, especially FEP+ , established their utility for pharmaceutical lead optimization. Herein, we propose a modified version of the ...FEP/REST (i.e., replica exchange with solute tempering) sampling protocol, based on detail studies on several targets by probing a large number of perturbations with different sampling schemes. Improved FEP+ binding affinity predictions for regular flexible-loop motions and considerable structural changes can be obtained by extending the prior to REST (pre-REST) sampling time from 0.24 ns/λ to 5 ns/λ and 2 × 10 ns/λ, respectively. With this new protocol, much more precise ∆∆G values of the individual perturbations, including the sign of the transformations and decreased error were obtained. We extended the REST simulations from 5 ns to 8 ns to achieve reasonable free energy convergence. Implementing REST to the entire ligand as opposed to solely the perturbed region, and also some important flexible protein residues (pREST region) in the ligand binding domain (LBD) has considerably improved the FEP+ results in most of the studied cases. Preliminary molecular dynamics (MD) runs were useful for establishing the correct binding mode of the compounds and thus precise alignment for FEP+ . Our improved protocol may further increase the FEP+ accuracy.
Halogen bonding has emerged at the forefront of advances in improving ligand: receptor interactions. In particular the newfound ability of this extant non-covalent-bonding phenomena has ...revolutionized computational approaches to drug discovery while simultaneously reenergizing synthetic approaches to the field. Here we survey, via examples of classical applications involving halogen atoms in pharmaceutical compounds and their biological hosts, the unique advantages that halogen atoms offer as both Lewis acids and Lewis bases.
Halogen bonding interactions between halogenated ligands and proteins were examined using the crystal structures deposited to date in the PDB. The data was analyzed as a function of halogen bonding ...to main chain Lewis bases, viz. oxygen of backbone carbonyl and backbone amide nitrogen. This analysis also examined halogen bonding to side-chain Lewis bases (O, N, and S) and to the electron-rich aromatic amino acids. All interactions were restricted to van der Waals radii with respective atoms. The data reveals that while fluorine and chlorine have strong tendencies favoring interactions with the backbone Lewis bases at glycine, the trend is not restricted to the achiral amino acid backbone for larger halogens. Halogen side-chain interactions are not restricted to amino acids containing O, N, and S as Lewis bases. Electron-rich aromatic amino acids host a high frequency of halogen bonds as does Leu. A closer examination of the latter hydrophobic side chain reveals that the “propensity of interactions” of halogen ligands at this oily residue is an outcome of strong classical halogen bonds with Lewis bases in the vicinity. Finally, an examination of Θ1 (C–X···O and C–X···N) and Θ2 (X···O–Z and X···N–Z) angles reveals that very few ligands adopt classical halogen bonding angles, suggesting that steric and other factors may influence these angles. The data is discussed in the context of ligand design for pharmaceutical applications.
Strategies for drug discovery and repositioning are urgently need with respect to COVID-19. Here we present REDIAL-2020, a suite of computational models for estimating small molecule activities in a ...range of SARS-CoV-2-related assays. Models were trained using publicly available, high-throughput screening data and by employing different descriptor types and various machine learning strategies. Here we describe the development and use of eleven models that span across the areas of viral entry, viral replication, live virus infectivity, in vitro infectivity and human cell toxicity. REDIAL-2020 is available as a web application through the DrugCentral web portal (http://drugcentral.org/Redial). The web application also provides similarity search results that display the most similar molecules to the query, as well as associated experimental data. REDIAL-2020 can serve as a rapid online tool for identifying active molecules for COVID-19 treatment.There is an urgent need to identify drugs that may be effective against SARS-CoV-2. A platform with a range of machine learning models is made available to predict anti-COVID-19 activity in candidate drugs and to help prioritize compounds for virtual screening.
The oncogenic activation of AKT gene has emerged as a key determinant of the aggressiveness of colorectal cancer (CRC); hence, research has focused on targeting AKT signaling for the treatment of ...advanced stages of CRC. In this study, we explored the anti-tumorigenic effects of withaferin A (WA) on CRC cells overexpressing AKT in preclinical (in vitro and in vivo) models. Our results indicated that WA, a natural compound, resulted in significant inhibition of AKT activity and led to the inhibition of cell proliferation, migration and invasion by downregulating the epithelial to mesenchymal transition (EMT) markers in CRC cells overexpressing AKT. The oral administration of WA significantly suppressed AKT-induced aggressive tumor growth in a xenograft model. Molecular analysis revealed that the decreased expression of AKT and its downstream pro-survival signaling molecules may be responsible for tumor inhibition. Further, significant inhibition of some important EMT markers, i.e., Snail, Slug, β-catenin and vimentin, was observed in WA-treated human CRC cells overexpressing AKT. Significant inhibition of micro-vessel formation and the length of vessels were evident in WA-treated tumors, which correlated with a low expression of the angiogenic marker RETIC. In conclusion, the present study emphasizes the crucial role of AKT activation in inducing cell proliferation, angiogenesis and EMT in CRC cells and suggests that WA may overcome AKT-induced cell proliferation and tumor growth in CRC.
Multiple scoring systems (including rank and score functions; MSS) have been widely used in multiple regression, intelligent biometric systems, multiple artificial neural nets, combining pattern ...classifiers, ensemble methods, machine learning and artificial intelligence (AI), data and information fusion, preference ranking, and deep learning. Combining MSS has achieved numerous successful results in a variety of domain applications. However, the reasons why this happens remains an active area of investigation. Combinatorial fusion analysis (CFA) combines MSS using the rank-score characteristic (RSC) function and cognitive diversity (CD). The RSC function was proposed to characterise the predictive behaviour of a scoring system. It was subsequently used to define the notion of "cognitive diversity", which measures the dissimilarity in the representation of information between two scoring systems. In this article, we first examine characterizations of and diversity between scoring systems. Then, we review combinatorial fusion analysis with a variety of domain applications, including biometric systems in cognitive neuroscience, and joint decision making with visual cognitive systems. Finally, we demonstrate that multi-layer combinatorial fusion (MCF) on the Kemeny rank space is a viable machine learning and AI framework for preference ranking and reinforcement learning. This work provides a scientific foundation and technological insights for the use of Combinatorial Fusion in ensemble methods, data and information fusion, preference ranking, and deep reinforcement learning with applications to a variety of domains in data science and informatics for secure and sustainable societies.
Superatom molecular orbitals (SAMOs) are atom-like molecular orbitals that have been observed in the buckminsterfullerene C60 molecule. We studied the ice-like water cluster (H2O)10 that is expected ...to be ubiquitous in nature in nanoscale microenvironments at ambient temperatures due to the nanoconfinement effect. We report for the first time the theoretical prediction of the existence of SAMOs in the adamantanoid nanostructured water cluster (H2O)10. The geometry of the adamantanoid water cluster (H2O)10 was optimized using the Restricted Hartree-Fock method and the ab-initio second-order Møller-Plesset perturbation theory (MP2) method, as well as the aqueous solvent phase polarizable continuum method (PCM). The optimized (H2O)10 structure is a distorted adamantanoid that closely matches the crystal structure of (H2O)10 that was previously reported. The theoretical studies using Hartree-Fock (HF), MP2, or Density Functional Theory (DFT) predict that the adamantanoid water cluster (H2O)10 exhibits SAMOs in the low-lying LUMOs. The orbital energies calculated with these methods are reported. The lowest-lying SAMOs in the water cluster (H2O)10 is the most intriguing SAMO due to its s-orbital character and potential to delocalize electrons in a large area that surrounds the cluster. The electron affinity of the water cluster (H2O)10 was calculated using HF, MP2, and DFT methods and the values obtained from each method were (kJ/mol) +74.71, -770.58, and -48.57, respectively. The existence of SAMOs in low-lying LUMO levels indicate of possible supramolecular chemistry of the water clusters with interfacial implications in nanoconfined spaces. Overall, these theoretical results predict new fundamental properties of water clusters that may have deep implications and impact in biological and nanotechnology systems that involve nanostructured water in confined spaces.
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Abstract
DrugCentral is a public resource (http://drugcentral.org) that serves the scientific community by providing up-to-date drug information, as described in previous papers. The current release ...includes 109 newly approved (October 2018 through March 2020) active pharmaceutical ingredients in the US, Europe, Japan and other countries; and two molecular entities (e.g. mefuparib) of interest for COVID19. New additions include a set of pharmacokinetic properties for ∼1000 drugs, and a sex-based separation of side effects, processed from FAERS (FDA Adverse Event Reporting System); as well as a drug repositioning prioritization scheme based on the market availability and intellectual property rights forFDA approved drugs. In the context of the COVID19 pandemic, we also incorporated REDIAL-2020, a machine learning platform that estimates anti-SARS-CoV-2 activities, as well as the ‘drugs in news’ feature offers a brief enumeration of the most interesting drugs at the present moment. The full database dump and data files are available for download from the DrugCentral web portal.
Cytochrome P450 2E1 (CYP2E1) plays a vital role in drug-induced hepatotoxicity and cancers (e.g. lung and bladder cancer), since it is responsible for metabolizing a number of medications and ...environmental toxins to reactive intermediate metabolites. CYP2E1 was recently found to be the highest expressed CYP enzyme in human livers using a proteomics approach, and CYP2E1-related toxicity is strongly associated with its protein level that shows significant inter-individual variability related to ethnicity, age, and sex. Furthermore, the expression of CYP2E1 demonstrates regulation by extensive genetic polymorphism, endogenous hormones, cytokines, xenobiotics, and varying pathological states. Over the past decade, the knowledge of pharmacology, toxicology, and biology about CYP2E1 has grown remarkably, but the research progress has yet to be summarized. This study presents a timely systematic review on CYP2E1's xenobiotic metabolism, genetic polymorphism, and inhibitors, with the focus on their clinical relevance for the efficacy and toxicity of various CYP2E1 substrates. Moreover, several knowledge gaps have been identified towards fully understanding the potential interactions among different CYP2E1 substrates in clinical settings. Through in-depth analyses of these knowns and unknowns, we expect this review will aid in future drug development and improve management of CYP2E1 related clinical toxicity.
Background
Halogen bonding has recently come to play as a target for lead optimization in rational drug design. However, most docking program don’t account for halogen bonding in their scoring ...functions and are not able to utilize this new approach. In this study a new and improved halogen bonding scoring function (XBSF) is presented along with its implementation in the AutoDock Vina molecular docking software. This new improved program is termed as AutoDock VinaXB, where XB stands for the halogen bonding parameters that were added.
Results
XBSF scoring function is derived based on the X···A distance and C–X···A angle of interacting atoms. The distance term was further corrected to account for the polar flattening effect of halogens. A total of 106 protein-halogenated ligand complexes were tested and compared in terms of binding affinity and docking poses using Vina and VinaXB. VinaXB performed superior to Vina in the majority of instances. VinaXB was closer to native pose both above and below 2 Å deviation categories almost twice as frequently as Vina.
Conclusions
Implementation of XBSF into AutoDock Vina has been shown to improve the accuracy of the docking result with regards to halogenated ligands. AutoDock VinaXB addresses the issues of halogen bonds that were previously being scored unfavorably due to repulsion factors, thus effectively lowering the output RMSD values.
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