Investigation of ligand selectivity in CYP3A7 by molecular dynamics simulations

Parameterization of General Organic Polymers within the Open Force Field Framework

Polymer and chemically modified biopolymer systems present unique challenges to traditional molecular simulation preparation workflows. First, typical polymer and biomolecular input formats, such as Protein Data Bank (PDB) files, lack adequate chemical information needed for the parameterization of new chemistries. Second, polymers are typically too large for accurate partial charge generation methods. In this work, we employ direct chemical perception through the Open Force Field toolkit to create a flexible polymer simulation workflow for organic polymers, encompassing everything from biopolymers to soft materials. We propose and test a new input specification for monomer information that can, along with a 3D conformational geometry, parametrize and simulate most soft-material systems within the same workflow used for smaller ligands. The monomer format encompasses a subset of the SMIRKS substructure query language to uniquely identify chemical information and repeating charges in underspecified systems through matching atomic connectivity. This workflow is combined with several different approaches for automatic partial-charge generation for larger systems. As an initial proof of concept, a variety of diverse polymeric systems were parametrized with the Open Force Field toolkit, including functionalized proteins, DNA, homopolymers, cross-linked systems, and sugars. Additionally, shape properties and radial distribution functions were computed from molecular dynamics simulations of poly(ethylene glycol), polyacrylamide, and poly(N-isopropylacrylamide) homopolymers in aqueous solution and compared to previous simulation results in order to demonstrate a start-to-finish workflow for simulation and property prediction. We expect that these tools will greatly expedite the day-to-day computational research of soft-matter simulations and create a robust atomic-scale polymer specification in conjunction with existing polymer structural notations.

Combined approach of homology modeling, molecular dynamics, and docking: computer-aided drug discovery

With the continuous development in software, algorithms, and increase in computer speed, the field of computer-aided drug design has been witnessing reduction in the time and cost of the drug designing process. Structure based drug design (SBDD), which is based on the 3D structure of the enzyme, is helping in proposing novel inhibitors. Although a number of crystal structures are available in various repositories, there are various proteins whose experimental crystallization is difficult. In such cases, homology modeling, along with the combined application of MD and docking, helps in establishing a reliable 3D structure that can be used for SBDD. In this review, we have reported recent works, which have employed these three techniques for generating structures and further proposing novel inhibitors, for cytoplasmic proteins, membrane proteins, and metal containing proteins. Also, we have discussed these techniques in brief in terms of the theory involved and the various software employed. Hence, this review can give a brief idea about using these tools specifically for a particular problem.

Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors

The Cytochrome P450 family of heme-containing proteins plays a major role in catalyzing phase I metabolic reactions, and the CYP3A4 subtype is responsible for the metabolism of many currently marketed drugs. Additionally, CYP3A4 has an inherent affinity for a broad spectrum of structurally diverse chemical entities, often leading to drug-drug interactions mediated by the inhibition or induction of the metabolic enzyme. The current study explores the binding of selected highly efficient CYP3A4 inhibitors by docking and molecular dynamics (MD) simulation protocols and their binding free energy calculated using the WaterSwap method. The results indicate the importance of binding pocket residues including Phe57, Arg105, Arg106, Ser119, Arg212, Phe213, Thr309, Ser312, Ala370, Arg372, Glu374, Gly481 and Leu483 for interaction with CYP3A4 inhibitors. The residue-wise decomposition of the binding free energy from the WaterSwap method revealed the importance of binding site residues Arg106 and Arg372 in the stabilization of all the selected CYP3A4-inhibitor complexes. The WaterSwap binding energies were further complemented with the MM(GB/PB)SA results and it was observed that the binding energies calculated by both methods do not differ significantly. Overall, our results could guide towards the use of multiple computational approaches to achieve a better understanding of CYP3A4 inhibition, subsequently leading to the design of highly specific and efficient new chemical entities with suitable ADMETox properties and reduced side effects.

Insight into the selective binding mechanism of DNMT1 and DNMT3A inhibitors: a molecular simulation study

DNA methyltransferases (DNMTs), responsible for the regulation of DNA methylation, have been regarded as promising drug targets for cancer therapy. However, high structural conservation of the catalytic domains of DNMTs poses a big challenge to design selective inhibitors for a specific DNMT isoform. In this study, molecular dynamics (MD) simulations, end-point free energy calculations and umbrella sampling (US) simulations were performed to reveal the molecular basis of the binding selectivity of three representative DNMT inhibitors towards DNMT1 and DNMT3A, including SFG (DNMT1 and DNMT3A dual inhibitors), DC-05 (DNMT1 selective inhibitor) and GSKex1 (DNMT3A selective inhibitor). The binding selectivity of the studied inhibitors reported in previous experiments is reproduced by the MD simulation and binding free energy prediction. The simulation results also suggest that the driving force to determine the binding selectivity of the studied inhibitors stems from the difference in the protein-inhibitor van der Waals interactions. Meanwhile, the per-residue free energy decomposition reveals that the contributions from several non-conserved residues in the binding pocket of DNMT1/DNMT3A, especially Val1580/Trp893, Asn1578/Arg891 and Met1169/Val665, are the key factors responsible for the binding selectivity of DNMT inhibitors. In addition, the binding preference of the studied inhibitors was further validated by the potentials of mean force predicted by the US simulations. This study will provide valuable information for the rational design of novel selective inhibitors targeting DNMT1 and DNMT3A.

Exploring the interactional details between aldose reductase (AKR1B1) and 3-Mercapto-5H-1,2,4-triazino[5,6-b]indole-5-acetic acid through molecular dynamics simulations

Aldose reductase (AKR1B1) has been considered as a significant target for designing drugs to counteract the development of diabetic complications. In the present study, molecular dynamics (MD) simulations and molecular mechanics generalized Born surface area (MM-GB/SA) calculations were performed to make sure which tautomer is the preferred one among three tautomeric forms (Mtia1, Mtia2, and Mtia3) of 3-Mercapto-5H-1,2,4-triazino[5,6-b]indole-5-acetic acid (Mtia) for binding to AKR1B1. The overall structural features and the results of calculated binding free energies indicate that Mtia1 and Mtia2 have more superiority than Mtia3 in terms of binding to AKR1B1. Furtherly, the local active site conformational characteristics and non-covalent interaction analysis were identified. The results indicate that the combination of Mtia2 and AKR1B1 is more stable than that of Mtia1. Furthermore, two extra hydrogen bonds between AKR1B1 and Mtia2 are found with respect to Mtia1. In addition, Mtia2 makes slightly stronger electrostatic interaction with the positively charged nicotinamide group of NADP⁺ than Mtia1. Based on the results above, Mtia2 is the preferred tautomeric form among the three tautomers. Our study can provide an insight into the details of the interaction between AKR1B1 and Mtia at the atomic level, and will be helpful for the further design of AKR1B1 inhibitors.

Theoretical design and investigation of 1,8-naphthalimide-based two-photon fluorescent probes for detecting cytochrome P450 1A with separated fluorescence signal

Two-photon fluorescent probe for detecting CYP1A enzyme with separated fluorescence signal.

In Silico Identification of Mimicking Molecules as Defense Inducers Triggering Jasmonic Acid Mediated Immunity against Alternaria Blight Disease in Brassica Species

Alternaria brassicae and Alternaria brassicicola are two major phytopathogenic fungi which cause Alternaria blight, a recalcitrant disease on Brassica crops throughout the world, which is highly destructive and responsible for significant yield losses. Since no resistant source is available against Alternaria blight, therefore, efforts have been made in the present study to identify defense inducer molecules which can induce jasmonic acid (JA) mediated defense against the disease. It is believed that JA triggered defense response will prevent necrotrophic mode of colonization of Alternaria brassicae fungus. The JA receptor, COI1 is one of the potential targets for triggering JA mediated immunity through interaction with JA signal. In the present study, few mimicking compounds more efficient than naturally occurring JA in terms of interaction with COI1 were identified through virtual screening and molecular dynamics simulation studies. A high quality structural model of COI1 was developed using the protein sequence of Brassica rapa. This was followed by virtual screening of 767 analogs of JA from ZINC database for interaction with COI1. Two analogs viz. ZINC27640214 and ZINC43772052 showed more binding affinity with COI1 as compared to naturally occurring JA. Molecular dynamics simulation of COI1 and COI1-JA complex, as well as best screened interacting structural analogs of JA with COI1 was done for 50 ns to validate the stability of system. It was found that ZINC27640214 possesses efficient, stable, and good cell permeability properties. Based on the obtained results and its physicochemical properties, it is capable of mimicking JA signaling and may be used as defense inducers for triggering JA mediated resistance against Alternaria blight, only after further validation through field trials.

Listeriosis downregulates hepatic cytochrome P450 enzymes in sublethal murine infection

PURPOSE

Listeria monocytogenes (Lm) can cross the intestinal barrier in humans and then disseminates into different organs. Invasion of the liver occurs even in sublethal infections, however, knowledge of affected physiological processes is scarce. This study employed a sublethal murine infection model to investigate liver responses systematically by proteomics.

EXPERIMENTAL DESIGN

Liver samples from three stages of the sublethal infection covering the initial invasion, the peak of infection, and the clearance phase (1, 3, 9 days postinoculation) were analyzed in comparison to samples from noninfected mice. Apart from flow cytometry and RT-PCRs for immune status control, liver responses were analyzed by quantitative peptide sequencing (HPLC-Orbitrap Fusion) using 4-plex iTRAQ-labeling.

RESULTS

Accurate MS characterized about 3600 proteins and statistics revealed 15% of the hepatic proteome as regulated. Immunological data as well as protein regulation dynamics strongly indicate stage-specific hepatic responses in sublethal infections. Most notably, this study detected a comprehensive deregulation of drug metabolizing enzymes at all stages, including 25 components of the cytochrome P450 system.

CONCLUSIONS AND CLINICAL RELEVANCE

Sublethal Lm infection deregulates hepatic drug metabolizing pathways. This finding indicates the need to monitor drug administration along Lm infections, especially in all patients needing constant medication.

Identification of potential inhibitors for AIRS from de novo purine biosynthesis pathway through molecular modeling studies - a computational approach

In cancer, de novo pathway plays an important role in cell proliferation by supplying huge demand of purine nucleotides. Aminoimidazole ribonucleotide synthetase (AIRS) catalyzes the fifth step of de novo purine biosynthesis facilitating in the conversion of formylglycinamidine ribonucleotide to aminoimidazole ribonucleotide. Hence, inhibiting AIRS is crucial due to its involvement in the regulation of uncontrollable cancer cell proliferation. In this study, the three-dimensional structure of AIRS from P. horikoshii OT3 was constructed based on the crystal structure from E. coli and the modeled protein is verified for stability using molecular dynamics for a time frame of 100 ns. Virtual screening and induced fit docking were performed to identify the best antagonists based on their binding mode and affinity. Through mutational studies, the residues necessary for catalytic activity of AIRS were identified and among which the following residues Lys35, Asp103, Glu137, and Thr138 are important in determination of AIRS function. The mutational studies help to understand the structural and energetic characteristics of the specified residues. In addition to Molecular Dynamics, ADME properties, binding free-energy, and density functional theory calculations of the compounds were carried out to find the best lead molecule. Based on these analyses, the compound from the NCI database, NCI_121957 was adjudged as the best molecule and could be suggested as the suitable inhibitor of AIRS. In future studies, experimental validation of these ligands as AIRS inhibitors will be carried out.

Prediction of a novel internal rearrangement of the insulin receptor

The insulin receptor (IR) plays critical roles in metabolism and growth, directed by the binding of insulin. Decades of research to understand the mechanism of insulin binding and activation of the IR have identified a region of the receptor, the C-terminal (CT) peptide, to be crucial for insulin binding. In particular, a truncated IR consisting of the first three domains fused to the CT peptide was found to bind insulin with nanomolar affinity, with undetectable binding in the absence of fused or soluble CT peptide. Problematically, all current crystal structures of the IR indicate the fusion point of the CT peptide to the three domains is located far from the position of the CT peptide as resolved in such structures. We have attempted to address this problem using molecular modelling and dynamics simulations. The results led to the identification of a potential inter-domain interaction between the L2 domain and the CT peptide that is not observed in any of the crystal structures of the IR. Investigations into this new interaction found a conformational change that could potentially be in response to insulin binding. Additionally, further simulation work with the new conformation demonstrated its compatibility with the position and orientation of insulin from the latest insulin-bound IR crystal structure.

Discovery of a regioselectivity switch in nitrating P450s guided by molecular dynamics simulations and Markov models

The dynamic motions of protein structural elements, particularly flexible loops, are intimately linked with diverse aspects of enzyme catalysis. Engineering of these loop regions can alter protein stability, substrate binding, and even dramatically impact enzyme function. When these flexible regions are structurally unresolvable, computational reconstruction in combination with large-scale molecular dynamics simulations can be used to guide the engineering strategy. Here, we present a collaborative approach consisting of both experiment and computation that led to the discovery of a single mutation in the F/G loop of the nitrating cytochrome P450 TxtE that simultaneously controls loop dynamics and completely shifts the enzyme's regioselectivity from the C4 to the C5 position of L-tryptophan. Furthermore, we find that this loop mutation is naturally present in a subset of homologous nitrating P450s and confirm that these uncharacterized enzymes exclusively produce 5-nitro-L-tryptophan, a previously unknown biosynthetic intermediate.

In-silico identification of inhibitors against mutated BCR-ABL protein of chronic myeloid leukemia: a virtual screening and molecular dynamics simulation study

Aberrant and proliferative expression of the oncogene BCR-ABL in the bone marrow cells had been proven as the prime cause of chronic myeloid leukemia (CML). It has been established that tyrosine kinase domain of BCR-ABL protein is a potential therapeutic target for the treatment of CML. Imatinib is considered as a first-generation drug that can inhibit the enzymatic action by inhibiting the ATP binding with BCR-ABL protein. Later on, insensitivity of CML cells towards Imatinib has been observed may be due to mutation in tyrosine kinase domain of the ABL receptor. Subsequently, some other second-generation drugs have also been reported viz. Baustinib, Nilotinib, Dasatinib, Ponatinib, Bafetinib, etc., which can able to combat against mutated domain of ABL tyrosine kinase protein. By taking into account of bioavailability and resistance developed, there is an utmost need to find some more inhibitors for the mutated ABL tyrosine kinase protein. For virtual screening, a data-set has been generated by collecting the all available drug like natural compounds from ZINC and Drug Bank databases. Comparative docking analysis was also carried out on the active site of ABL tyrosine kinase receptor with reported reference inhibitors. Molecular dynamics simulation of the best screened interacting complex was done for 50 ns to validate the stability of the system. These selected inhibitors were further validated and analyzed through pharmacokinetics properties and series of ADMET parameters by in silico methods. Considering the above said parameters proposed molecules are concluded as potential leads for drug designing pipeline against CML.

Exploring dual inhibitors for STAT1 and STAT5 receptors utilizing virtual screening and dynamics simulation validation

Signal transducer and activator of transcription (STAT) proteins are latent cytoplasmic transcription factors that transduce signals from cytokines and growth factors to the nucleus and thereby regulate the expression of a variety of target genes. Although mutations of STATs have not been reported in human tumors but the activity of several members of the family, such as STAT1 and STAT5, is deregulated in a variety of human carcinoma. STAT1 and STAT5 share a structural similarity with a highly conserved SH2 domain which is responsible for the activation of STAT proteins on interaction with phosphotyrosine motifs for specific STAT-receptor contacts and STAT dimerization. The purpose of this study is to identify domain-specific dual inhibitors for both STAT1 and STAT5 proteins from a database of natural products and natural product-like compounds comprising of over 90,000 compounds. Virtual screening-based molecular docking was performed in order to find novel natural dual inhibitors. Further, the study was supported by the 50-ns molecular dynamics simulation for receptor-ligand complexes (STAT1-STOCK-1N-69677 and STAT5-STOCK-1N-69677). Analysis of molecular interactions in the SH2 domains of both STAT1 and STAT5 proteins with the ligand revealed few conserved amino acid residues which are responsible to stabilize the ligands within the binding pocket through bonded and non-bonded interactions. This study suggested that compound STOCK-1N-69677 might putatively act as a dual inhibitor of STAT1 and STAT5 receptors, through its binding to the SH2 domain.