Computational structure‐based drug design: Predicting target flexibility

The role of molecular modeling in drug design has experienced a significant revamp in the last decade. The increase in computational resources and molecular models, along with software developments, is finally introducing a competitive advantage in early phases of drug discovery. Medium and small companies with strong focus on computational chemistry are being created, some of them having introduced important leads in drug design pipelines. An important source for this success is the extraordinary development of faster and more efficient techniques for describing flexibility in three‐dimensional structural molecular modeling. At different levels, from docking techniques to atomistic molecular dynamics, conformational sampling between receptor and drug results in improved predictions, such as screening enrichment, discovery of transient cavities, etc. In this review article we perform an extensive analysis of these modeling techniques, dividing them into high and low throughput, and emphasizing in their application to drug design studies. We finalize the review with a section describing our Monte Carlo method, PELE, recently highlighted as an outstanding advance in an international blind competition and industrial benchmarks.We acknowledge the BSC-CRG-IRB Joint Research Program in Computational Biology. This work was supported by a grant from the Spanish Government CTQ2016-79138-R.J.I. acknowledges support from SVP-2014-068797, awarded by the Spanish Government.Peer ReviewedPostprint (author's final draft

Personalized medicine : the impact on chemistry

An effective strategy for personalized medicine requires a major conceptual change in the development and application of therapeutics. In this article, we argue that further advances in this field should be made with reference to another conceptual shift, that of network pharmacology. We examine the intersection of personalized medicine and network pharmacology to identify strategies for the development of personalized therapies that are fully informed by network pharmacology concepts. This provides a framework for discussion of the impact personalized medicine will have on chemistry in terms of drug discovery, formulation and delivery, the adaptations and changes in ideology required and the contribution chemistry is already making. New ways of conceptualizing chemistry’s relationship with medicine will lead to new approaches to drug discovery and hold promise of delivering safer and more effective therapies

Pharmacologic Activities of 3’-Hydroxypterostilbene: Cytotoxic, Anti- Oxidant, Anti-Adipogenic, Anti-Inflammatory, Histone Deacetylase and Sirtuin 1 Inhibitory Activity

Purpose: Delineate the selected pharmacodynamics of a naturally occurring stilbene 3’- Hydroxypterostilbene. Objective: Characterize for the first time the pharmacodynamics bioactivity in several in-vitro assays with relevant roles in heart disease, inflammation, cancer, and diabetes etiology and pathophysiology. Methods: 3’-Hydroxypterostilbene was studied in in-vitro assays to identify possible bioactivity. Results: 3’-Hydroxypterostilbene demonstrated anti-oxidant, anti-inflammatory, cytotoxic, antiadipogenic, histone deacetylase, and sirtuin-1 inhibitory activity. Conclusions: The importance of understanding individual stilbene pharmacologic activities were delineated. Small changes in chemical structure of stilbene compounds result in significant pharmacodynamic differences

Comparing sixteen scoring functions for predicting biological activities of ligands for protein targets

Accurately predicting relative binding affinities and biological potencies for ligands that interact with proteins remains a significant challenge for computational chemists. Most evaluations of docking and scoring algorithms have focused on enhancing ligand affinity for a protein by optimizing docking poses and enrichment factors during virtual screening. However, there is still relatively limited information on the accuracy of commercially available docking and scoring software programs for correctly predicting binding affinities and biological activities of structurally related inhibitors of different enzyme classes. Presented here is a comparative evaluation of eight molecular docking programs (Autodock Vina, Fitted, FlexX, Fred, Glide, GOLD, LibDock, MolDock) using sixteen docking and scoring functions to predict the rank-order activity of different ligand series for six pharmacologically important protein and enzyme targets (Factor Xa, Cdk2 kinase, Aurora A kinase, COX-2, pla2g2a, β Estrogen receptor). Use of Fitted gave an excellent correlation (Pearson 0.86, Spearman 0.91) between predicted and experimental binding only for Cdk2 kinase inhibitors. FlexX and GOLDScore produced good correlations (Pearson > 0.6) for hydrophilic targets such as Factor Xa, Cdk2 kinase and Aurora A kinase. By contrast, pla2g2a and COX-2 emerged as difficult targets for scoring functions to predict ligand activities. Although possessing a high hydrophobicity in its binding site, β Estrogen receptor produced reasonable correlations using LibDock (Pearson 0.75, Spearman 0.68). These findings can assist medicinal chemists to better match scoring functions with ligand-target systems for hit-to-lead optimization using computer-aided drug design approaches

Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics

This book is a collection of original research articles in the field of computer-aided drug design. It reports the use of current and validated computational approaches applied to drug discovery as well as the development of new computational tools to identify new and more potent drugs

From a Molecule to a Drug: Chemical Features Enhancing Pharmacological Potential

This book collects contributions published in the Special Issue “From a Molecule to a Drug: Chemical Features Enhancing Pharmacological Potential” and dealing with successful stories of drug improvement or design using classic protocols, quantum mechanical mechanistic investigation, or hybrid approaches such as QM/MM or QM/ML (machine learning). In the last two decades, computer-aided modeling has strongly supported scientists’ intuition to design functional molecules. High-throughput screening protocols, mainly based on classical mechanics’ atomistic potentials, are largely employed in biology and medicinal chemistry studies with the aim of simulating drug-likeness and bioactivity in terms of efficient binding to the target receptors. The advantages of this approach are quick outcomes, the possibility of repurposing commercially available drugs, consolidated protocols, and the availability of large databases. On the other hand, these studies do not intrinsically provide reactivity information, which requires quantum mechanical methodologies that are only applicable to significantly smaller and simplified systems at present. These latter studies focus on the drug itself, considering the chemical properties related to its structural features and motifs. Overall, such simulations provide necessary insights for a better understanding of the chemistry principles that rule the diseases at the molecular level, as well as possible mechanisms for restoring the physiological equilibrium

The Effects Of Bone Marrow Adipocytes On Metabolic Regulation In Metastatic Prostate Cancer

Bone is a preferential site of metastasis from prostate cancer (PCa). Although there have been many advances in therapeutic options for patients suffering from metastatic PCa, this disease remains incurable with an estimated five-year survival of 33%. To design effective therapeutic interventions for metastatic PCa, it is essential that we elucidate the molecular mechanisms responsible for tumor cell adaptation to and the ability to thrive within the bone metastatic niche. Age and obesity, conditions that increase adipocyte numbers in bone marrow, are risk factors for skeletal metastases from PCa; therefore, our laboratory is focused on the interactions between marrow adipocytes and PCa cells. We initially detailed the metabolic alterations that occur in prostate cancer cells in response to interactions with bone marrow adipocytes in multiple in vivo and in vitro models. The following conclusions were drawn as a result of these experiments: 1) Patients with metastatic disease have increased expression of glycolytic and hypoxic genes compared to primary PCa tumors; 2) tumors grown intratibially in vivo in diet induced models of high marrow adiposity have increased expression of glycolytic and hypoxic genes compared to mice with fewer marrow adipocytes; 3) paracrine interactions between tumor cells and adipocytes in vitro induce expression of glycolytic and hypoxic proteins in tumor cells; 4) PCa cells exposed to adipocytes with increased expression of glycolytic markers exhibit enhanced Warburg metabolism with increases in lactate production, decreases in oxidative phosphorylation, and decreases in ATP production without perturbation of mitochondrial integrity or cellular viability; 5) tumor cells stimulate lipolysis within adipocytes but the inhibition of lipolysis does not affect adipocyte-driven changes in PCa cell metabolism due to possible compensatory mechanisms; 6) metabolic effects are driven through the activation of HIF-1α in PCa cells as shown by increased expression of hypoxia-responsive genes and the reversal of adipocyte-induced metabolic changes upon knockdown of tumor cell HIF-1α. Additionally, we found novel signaling pathways are activated in tumor cells due to cross talk between tumor cells and adipocytes. We observed a regulation of COX-2 in adipocytes by tumor-secreted IL-1β that leads to increased PGE2 synthesis and release and this PGE2 signals through the EP receptors on the tumor cells to elicit downstream GSK3β/β-catenin signaling and subsequent HIF-1α activation. We also observed increased SPHK1 in adipocytes exposed to tumor cells as an effect of tumor-stimulated lipolysis within adipocytes, but that S1P was not sufficient to activate HIF-1α signaling in tumor cells or downstream metabolic alterations. In summary, we have discovered novel crosstalk between metastatic prostate tumor cells and bone marrow adipocytes that cause activation of many pathways involved in tumor survival and growth within the bone. We have revealed a functional contribution of bone marrow adipocytes to altered tumor metabolism and signaling in bone. The expected outcome of this research is the validation of the significance of adipocyte-derived lipids in growth and aggressiveness of metastatic PCa in bone. The ultimate goal is utilize findings from this study to explore whether adipocyte-driven metabolic adaptation contributes to chemoresistance of skeletal tumors and whether targeting tumor metabolism offers new options for improved therapy and/or prevention of aggressive disease

Applications of the indole scaffold in medicinal chemistry: development of new antioxidants, COX inhibitors and antitubercular agents

Dissertação para obtenção do Grau de Doutor em Química, especialidade Química OrgânicaFundação para a Ciência e Tecnologia - SFRH/BD/46234/200

Propanil (3,4-DCPA)-induced alterations of macrophage function

The pesticide 3,4-dichloropropionanilide (propanil or alternatively, DCPA) is a post-emergent herbicide predominantly used for the control of weeds on commercial rice crops worldwide. The US Environmental Protection Agency report on Pesticides Industry Sales and Usage in 2001 ranked propanil as the 17th most used herbicide in the US. It is applied on the fields via groundboom sprayers or aerial equipment suppressing photosynthesis and carbon fixation of a growing plant. The primary target of herbicide exposure is personnel working in the manufacturing and application who are required to wear personal protective equipment to minimize the exposure. The common routes of this exposure are inhalational and dermal, and to a lesser extent, oral. A number of toxic side effects are induced by propanil include hemolytic anemia, methemoglobinemia, and myelotoxicity. The majority of current knowledge about propanil\u27s toxic effects comes from animal studies. Liver and spleen were found to be the primary target organs, with many cell populations of the immune system affected, including T and B lymphocytes, NK cells and macrophages.;Macrophages play essential roles in both innate and adaptive immune responses. They recognize and destroy pathogens through phagocytosis and generation of reactive oxygen and nitrogen species (ROS and RNS). Macrophages can also function as antigen presenting cells in the initiation of an adaptive immune response and secrete a number of cytokines and inflammatory mediators thereby modulating the immune reaction at the inflamed site.;Previous studies have demonstrated that propanil was able to suppress interleukin (IL)-1beta, IL-6 and TNF-alpha cytokine production by LPS-activated murine macrophages. The analysis of nuclear factor-kappaB (NF-kappaB), responsible for TNF-alpha production, detected a decreased nuclear localization of NF-kappaB accompanied by a reduced, but not entirely abrogated binding to DNA activity.;The first study of this dissertation demonstrated the ability of propanil to inhibit TNF-alpha production by LPS-stimulated human monocytic cells line and suppress phagocytosis of fluorescent beads and Listeria monocytogenes . The ability to directly kill this bacterium and produce ROS and RNS was also assessed. The results demonstrate that DCPA has profound effects on macrophage function, and provide insight into the potential mechanisms of immunosuppression by DCPA. The second study focused on the mechanism of dramatic suppression of an inflammatory mediator secreted by activated macrophages, prostaglandin E2 (PGE2). Enzymatic activity and expression level of the proteins involved in PGE2 production were studied. However, the exact mechanism of propanil\u27s action is still unknown. The third study describes a novel behavior on NF-kappaB, called oscillations, in continuously LPS-stimulated macrophages. Binding activity of NF-kappaB was studied by two independent methods, and a mathematical model describing the oscillatory behavior was created based on experimental data. It demonstrated that propanil exposure potentiated the NF-kappaB activation process changing the oscillation behavior which could influence the transcription activity of the NF-kappaB-inducible genes.;Taken together our findings indicate that propanil exposure affects a number of important macrophage functions, such as phagocytosis, ROS and RNS production and inflammatory mediator\u27s secretion. Our studies also demonstrated a potential mechanism for the inhibition of a number of inflammatory cytokines through changes in NF-kappaB binding activity and oscillatory behavior