QXP: powerful, rapid computer algorithms for structure-based drug design

An insight into advances and challenges in the development of potential stearoyl Co-A desaturase 1 inhibitors

Stearoyl-CoA desaturase 1 (SCD1) is one of the key enzymes involved in lipid metabolism, plays a vital role in the synthesis of monounsaturated fatty acids (MUFAs) from saturated fatty acids (SFAs). Due to its promising therapeutic potential in treating metabolic disorders, cancers, and skin diseases there is an increasing interest in the development of novel inhibitors against SCD1. This review comprehensively explores the evolution of potential SCD1 inhibitors, focusing on systemic and liver-targeted inhibitors and discusses their structure-activity relationship (SAR) pattern. Among the various small molecules reported, natural products like sterculic acid have emerged as significant SCD1 inhibitors, highlighting the potential of naturally derived compounds in therapeutic development. This review also addresses the challenges in optimizing pharmacokinetic properties and reducing adverse effects, providing insights into the future directions for the development of potential novel SCD1 inhibitors with maximum therapeutic effect and minimum side effects.

Molecular docking approaches and its significance in assessing the antioxidant properties in different compounds

In the last few years, the significance of antioxidant compounds and their properties has attracted great interest from the scientific community. The role of an antioxidant in managing & regulating oxidative stress and also in the protection of the human body from severe adverse effects due to excess release of free radicles or reactive oxygen species (ROS) is remarkable. From aiding protection & combating severe illnesses such as cancer, neurodegeneration, aging, and diabetes to being a vital part of the treatment of SARs-CoV-19 is of great importance. Therefore, the study of anti-oxidants is of great importance in human sustenance. Additionally, molecular docking techniques and their various mathematical features help in understanding the molecular interactions of anti-oxidants based on their lowest binding energy. The evaluation of the binding score between two constituent molecules will provide insight as to the binding process and also suggest possible novel therapeutic targets for the treatment of diseases. In this chapter, we will discuss the significance of molecular docking techniques in the study of antioxidant compounds.

Biophysical Survey of Small-Molecule β-Catenin Inhibitors: A Cautionary Tale

The canonical Wingless-related integration site signaling pathway plays a critical role in human physiology, and its dysregulation can lead to an array of diseases. β-Catenin is a multifunctional protein within this pathway and an attractive yet challenging therapeutic target, most notably in oncology. This has stimulated the search for potent small-molecule inhibitors binding directly to the β-catenin surface to inhibit its protein–protein interactions and downstream signaling. Here, we provide an account of the claimed (and some putative) small-molecule ligands of β-catenin from the literature. Through in silico analysis, we show that most of these molecules contain promiscuous chemical substructures notorious for interfering with screening assays. Finally, and in line with this analysis, we demonstrate using orthogonal biophysical techniques that none of the examined small molecules bind at the surface of β-catenin. While shedding doubts on their reported mode of action, this study also reaffirms β-catenin as a prominent target in drug discovery.

Single-Walled Carbon Nanotubes Inhibit TRPC4-Mediated Muscarinic Cation Current in Mouse Ileal Myocytes

Single-walled carbon nanotubes (SWCNTs) are characterized by a combination of rather unique physical and chemical properties, which makes them interesting biocompatible nanostructured materials for various applications, including in the biomedical field. SWCNTs are not inert carriers of drug molecules, as they may interact with various biological macromolecules, including ion channels. To investigate the mechanisms of the inhibitory effects of SWCNTs on the muscarinic receptor cation current (mI_CAT), induced by intracellular GTPγs (200 μM), in isolated mouse ileal myocytes, we have used the patch-clamp method in the whole-cell configuration. Here, we use molecular docking/molecular dynamics simulations and direct patch-clamp recordings of whole-cell currents to show that SWCNTs, purified and functionalized by carboxylation in water suspension containing single SWCNTs with a diameter of 0.5–1.5 nm, can inhibit mI_CAT, which is mainly carried by TRPC4 cation channels in ileal smooth muscle cells, and is the main regulator of cholinergic excitation–contraction coupling in the small intestinal tract. This inhibition was voltage-independent and associated with a shortening of the mean open time of the channel. These results suggest that SWCNTs cause a direct blockage of the TRPC4 channel and may represent a novel class of TRPC4 modulators.

Novel drug design and bioinformatics: an introduction

In the current era of high-throughput technology, where enormous amounts of biological data are generated day by day via various sequencing projects, thereby the staggering volume of biological targets deciphered. The discovery of new chemical entities and bioisosteres of relatively low molecular weight has been gaining high momentum in the pharmacopoeia, and traditional combinatorial design wherein chemical structure is used as an initial template for enhancing efficacy pharmacokinetic selectivity properties. Once the compound is identified, it undergoes ADMET filtration to ensure whether it has toxic and mutagenic properties or not. If the compound has no toxicity and mutagenicity is either considered a potential lead molecule. Understanding the mechanism of lead molecules with various biological targets is imperative to advance related functions for drug discovery and development. Notwithstanding, a tedious and costly process, taking around 10–15 years and costing around $4 billion, cascaded approached of Bioinformatics and Computational biology viz., structure-based drug design (SBDD) and cognate ligand-based drug design (LBDD) respectively rely on the availability of 3D structure of target biomacromolecules and vice versa has made this process easy and approachable. SBDD encompasses homology modelling, ligand docking, fragment-based drug design and molecular dynamics, while LBDD deals with pharmacophore mapping, QSAR, and similarity search. All the computational methods discussed herein, whether for target identification or novel ligand discovery, continuously evolve and facilitate cost-effective and reliable outcomes in an era of overwhelming data.

Overcoming the Pregnane X Receptor Liability: Rational Design to Eliminate PXR-Mediated CYP Induction

The pregnane X receptor (PXR) regulates expression of proteins responsible for all three phases required for the detoxification mechanism, which include CYP450 enzymes, phase II enzymes, and multidrug efflux pumps. Therefore, PXR is a prominent receptor that is responsible for xenobiotic excretion and drug-drug interactions. Pyrimidinone 1 is an antagonist of the calcium sensing receptor (CaSR) and a strong activator of PXR. Repeat oral administration revealed diminished exposures over time, which prohibited further progression. A medicinal chemistry campaign was initiated to understand and abolish activation of PXR in order to increase systemic exposures. Rational structure-activity relationship investigations utilizing cocrystal structures and a de novo pharmacophore model resulted in compounds devoid of PXR activation. These studies culminated in the first orally active CaSR antagonist 8 suitable for progression. Cocrystallography, the pharmacophore model employed, and additional observations reported herein supported rational elimination of PXR activation and have applicability across diverse chemical classes to help erase PXR-driven drug-drug interactions.

C60 fullerene against SARS-CoV-2 coronavirus: an in silico insight

Based on WHO reports the new SARS-CoV-2 coronavirus is currently widespread all over the world. So far > 162 million cases have been confirmed, including > 3 million deaths. Because of the pandemic still spreading across the globe the accomplishment of computational methods to find new potential mechanisms of virus inhibitions is necessary. According to the fact that C60 fullerene (a sphere-shaped molecule consisting of carbon) has shown inhibitory activity against various protein targets, here the analysis of the potential binding mechanism between SARS-CoV-2 proteins 3CLpro and RdRp with C60 fullerene was done; it has resulted in one and two possible binding mechanisms, respectively. In the case of 3CLpro, C60 fullerene interacts in the catalytic binding pocket. And for RdRp in the first model C60 fullerene blocks RNA synthesis pore and in the second one it prevents binding with Nsp8 co-factor (without this complex formation, RdRp can't perform its initial functions). Then the molecular dynamics simulation confirmed the stability of created complexes. The obtained results might be a basis for other computational studies of 3CLPro and RdRp potential inhibition ways as well as the potential usage of C60 fullerene in the fight against COVID-19 disease.

Small-molecule inhibitors of the PDZ domain of Dishevelled proteins interrupt Wnt signalling

Dishevelled (Dvl) proteins are important regulators of the Wnt signalling pathway, interacting through their PDZ domains with the Wnt receptor Frizzled. Blocking the Dvl PDZ-Frizzled interaction represents a potential approach for cancer treatment, which stimulated the identification of small-molecule inhibitors, among them the anti-inflammatory drug Sulindac and Ky-02327. Aiming to develop tighter binding compounds without side effects, we investigated structure-activity relationships of sulfonamides. X-ray crystallography showed high complementarity of anthranilic acid derivatives in the GLGF loop cavity and space for ligand growth towards the PDZ surface. Our best binding compound inhibits Wnt signalling in a dose-dependent manner as demonstrated by TOP-GFP assays (IC50 ∼ 50  µ M ) and Western blotting of β -catenin levels. Real-time PCR showed reduction in the expression of Wnt-specific genes. Our compound interacted with Dvl-1 PDZ (KD = 2.4  µ M ) stronger than Ky-02327 and may be developed into a lead compound interfering with the Wnt pathway.

Spontaneous Selection of Cryptosporidium Drug Resistance in a Calf Model of Infection

The intestinal protozoan Cryptosporidium is a leading cause of diarrheal disease and mortality in young children. There is currently no fully effective treatment for cryptosporidiosis, which has stimulated interest in anticryptosporidial development over the last ∼10 years, with numerous lead compounds identified, including several tRNA synthetase inhibitors. Here, we report the results of a dairy calf efficacy trial of the methionyl-tRNA (Cryptosporidium parvum MetRS [CpMetRS]) synthetase inhibitor 2093 and the spontaneous emergence of drug resistance. Dairy calves experimentally infected with Cryptosporidium parvum initially improved with 2093 treatment, but parasite shedding resumed in two of three calves on treatment day 5. Parasites shed by each recrudescent calf had different amino acid-altering mutations in the gene encoding CpMetRS (CpMetRS), yielding either an aspartate 243-to-glutamate (D243E) or a threonine 246-to-isoleucine (T246I) mutation. Transgenic parasites engineered to have either the D243E or T246I CpMetRS mutation using CRISPR/Cas9 grew normally but were highly 2093 resistant; the D243E and T246I mutant-expressing parasites, respectively, had 2093 half-maximal effective concentrations (EC₅₀s) that were 613- and 128-fold that of transgenic parasites with wild-type CpMetRS. In studies using recombinant enzymes, the D243E and T246I mutations shifted the 2093 IC₅₀ >170-fold. Structural modeling of CpMetRS based on an inhibitor-bound Trypanosoma brucei MetRS crystal structure suggested that the resistance mutations reposition nearby hydrophobic residues, interfering with compound binding while minimally impacting substrate binding. This is the first report of naturally emerging Cryptosporidium drug resistance, highlighting the need to address the potential for anticryptosporidial resistance and establish strategies to limit its occurrence.

C60 Fullerene Governs Doxorubicin Effect on Metabolic Profile of Rat Microglial Cells In Vitro

Background: C₆₀ fullerenes and their derivatives are actively investigated for the use in neuroscience. Applications of these nanoscale materials require the examination of their interaction with different neural cells, especially with microglia, because these cells, like other tissue resident phagocytes, are the earliest and most sensitive responders to nanoparticles. The aim of this study was to investigate the effect of C₆₀ fullerene and its nanocomplex with doxorubicin (Dox) on the metabolic profile of brain-resident phagocytes-microglia-in vitro. Methods: Resting microglial cells from adult male Wistar rats were used in experiments. Potential C₆₀ fullerene targets in microglial cells were studied by computer simulation. Microglia oxidative metabolism and phagocytic activity were examined by flow cytometry. Griess reaction and arginase activity colorimetric assay were used to explore arginine metabolism. Results: C₆₀ fullerene when used alone did not influence microglia oxidative metabolism and phagocytic activity but shifted arginine metabolism toward the decrease of NO generation. Complexation of C₆₀ fullerene with Dox (C₆₀-Dox) potentiated the ability of the latter to stimulate NO generation. Conclusion: The capability of C₆₀ fullerenes used alone to cause anti-inflammatory shift of microglia arginine metabolism makes them a promising agent for the correction of neuroinflammatory processes involved in neurodegeneration. The potentiating action of C₆₀ fullerene on the immunomodulatory effect of Dox allows us to consider the C₆₀ molecule as an attractive vehicle for this antitumor agent.

Molecular Docking: Challenges, Advances and its Use in Drug Discovery Perspective

Molecular docking is a process through which small molecules are docked into the macromolecular structures for scoring its complementary values at the binding sites. It is a vibrant research area with dynamic utility in structure-based drug-designing, lead optimization, biochemical pathway and for drug designing being the most attractive tools. Two pillars for a successful docking experiment are correct pose and affinity prediction. Each program has its own advantages and drawbacks with respect to their docking accuracy, ranking accuracy and time consumption so a general conclusion cannot be drawn. Moreover, users don't always consider sufficient diversity in their test sets which results in certain programs to outperform others. In this review, the prime focus has been laid on the challenges of docking and troubleshooters in existing programs, underlying algorithmic background of docking, preferences regarding the use of docking programs for best results illustrated with examples, comparison of performance for existing tools and algorithms, state of art in docking, recent trends of diseases and current drug industries, evidence from clinical trials and post-marketing surveillance are discussed. These aspects of the molecular drug designing paradigm are quite controversial and challenging and this review would be an asset to the bioinformatics and drug designing communities.

Synthesis, biological evaluation, and modeling studies of 1,3-disubstituted cyclobutane-containing analogs of combretastatin A4

With the aim of circumventing the adverse cis/trans-isomerization of combretastatin A4 (CA4), a naturally occurring tumor-vascular disrupting agent, we designed novel CA4 analogs bearing 1,3-cyclobutane moiety instead of the cis-stilbene unit of the parent compound. The corresponding cis and trans cyclobutane-containing derivatives were prepared as pure diastereomers. The structure of the target compounds was confirmed by X-ray diffraction study. The title compounds were evaluated for their cytotoxic properties in human cancer cell lines HepG2 (hepatocarcinoma) and SK-N-DZ (neuroblastoma), and the overall activity was found in micromolar range. Molecular docking studies and molecular dynamics simulation within the colchicine binding site of tubulin were in good agreement with the obtained cytotoxicity data.

Water-Soluble Pristine C60 Fullerenes Inhibit Liver Fibrotic Alteration and Prevent Liver Cirrhosis in Rats

Liver cirrhosis is an outcome of a wide range of liver chronic diseases. It is attributed to oxidative stress; therefore, antioxidant usage could be a promising treatment of that. So, exploring the impact of effective free radical scavenger pristine C₆₀ fullerenes on liver fibrosis and cirrhosis and their ability to interact with main growth factor receptors involved in liver fibrogenesis was aimed to be discovered. We used N-diethylnitrosamine/carbon tetrachloride-induced simulations of rat liver fibrosis (10 weeks) and cirrhosis (15 weeks). Pristine C₆₀ fullerene aqueous colloid solution (C₆₀FAS) was injected daily at a dose of 0.25 mg/kg throughout the experiment. Liver morphology and functional and redox states were assessed. C₆₀ fullerenes' ability to interact with epidermal, vasoendothelial, platelet-derived, and fibroblast growth factor receptors (EGFR, VEGFR, PDGFR, and FGFR, respectively) was estimated by computational modeling. We observed that C₆₀FAS reduced the severity of fibrosis in fibrotic rats (0.75 vs. 3.0 points according to Ishak score), attenuated the hepatocyte injury, normalized elevated blood serum alkaline phosphatase (ALP) and lactate dehydrogenase (LDH), and mitigated oxidative stress manifestation in liver tissue restoring its redox balance. When applied to cirrhotic animals, C₆₀FAS reduced connective tissue deposition as well (2.4 vs. 5.4 points according to Ishak score), diminished ALP and LDH (by 16% and 61%), and normalized conjugated and nonconjugated bilirubin, restoring the liver function. Altered liver lipid and protein peroxides and glutathione peroxidase activity were also leveled. Within a computer simulation, it was shown that C₆₀ fullerenes can block hinge prohibiting ATP binding for EGFR and FGFR and thus blocking associated signal pathways. This ability in addition to their antioxidant properties may contribute to C₆₀ fullerene's antifibrotic action. Thus, C₆₀FAS may have a substantial therapeutic potential as an inhibitor of liver fibrosis and cirrhosis.

Pyrrole derivatives as potential anti-cancer therapeutics: synthesis, mechanisms of action, safety

Pyrrole derivatives (PDs) chloro-1-(4-chlorobenzyl)-4-((3-(trifluoromethyl)phenyl)amino)-1H-pyrrole-2,5-dione (MI-1) and 5-amino-4-(1,3-benzothyazol-2-yn)-1-(3-methoxyphenyl)-1,2-dihydro-3H-pyrrole-3-one (D1) were synthesised as inhibitors of several protein kinases including EGFR and VEGFR. The aim of the study was to reveal the exact mechanisms of PDs' action EGFR and VEGFR are involved in. We observed, that both PDs could bind with EGFR and VEGFR and form stable complexes. PDs entered into electrostatic interactions with polar groups of phospholipid heads in cell membrane, and the power of interaction depended on the nature of PD radical substituents (greater for MI-1 and smaller for D1). Partial intercalation of MI-1 into the membrane hydrophobic zone also occurred. PDs concentrations induced apoptosis in malignant cells but normal ones had different sensitivity to those. MI-1 and D1 acted like antioxidants in inflamed colonic tissue, as evidenced by reduce of lipid and protein peroxidation products (by 43-67%) and increase of superoxide dismutase activity (by 40 and 58%) with restoring these values to control ones. MI-1 restored reduced haemoglobin and normalised elevated platelets and monocytes in settings of colorectal cancer, whereas D1 normalised only platelets. Thus, MI-1 and D1 could be used as competitive inhibitors of EGFR and VEGFR and antioxidants, which might contribute to realisation of their anti-inflammatory, proapoptotic and antitumor activity.

Optimization and Evaluation of Site-Identification by Ligand Competitive Saturation (SILCS) as a Tool for Target-Based Ligand Optimization

Chemical fragment cosolvent sampling techniques have become a versatile tool in ligand-protein binding prediction. Site-identification by ligand competitive saturation (SILCS) is one such method that maps the distribution of chemical fragments on a protein as free energy fields called FragMaps. Ligands are then simulated via Monte Carlo techniques in the field of the FragMaps (SILCS-MC) to predict their binding conformations and relative affinities for the target protein. Application of SILCS-MC using a number of different scoring schemes and MC sampling protocols against multiple protein targets was undertaken to evaluate and optimize the predictive capability of the method. Seven protein targets and 551 ligands with broad chemical variability were used to evaluate and optimize the model to maximize Pearson's correlation coefficient, Pearlman's predictive index, correct relative binding affinity, and root-mean-square error versus the absolute experimental binding affinities. Across the protein-ligand sets, the relative affinities of the ligands were predicted correctly an average of 69% of the time for the highest overall SILCS protocol. Training the FragMap weighting factors using a Bayesian machine learning (ML) algorithm led to an increase to an average 75% relative correct affinity predictions. Furthermore, once the optimal protocol is identified for a specific protein-ligand system average predictabilities of 76% are achieved. The ML algorithm is successful with small training sets of data (30 or more compounds) due to the use of physically correct FragMap weights as priors. Notably, the 76% correct relative prediction rate is similar to or better than free energy perturbation methods that are significantly computationally more expensive than SILCS. The results further support the utility of SILCS as a powerful and computationally accessible tool to support lead optimization and development in drug discovery.

C60 fullerenes selectively inhibit BKCa but not Kv channels in pulmonary artery smooth muscle cells

Possessing unique physical and chemical properties, C₆₀ fullerenes are arising as a potential nanotechnological tool that can strongly affect various biological processes. Recent molecular modeling studies have shown that C₆₀ fullerenes can interact with ion channels, but there is lack of data about possible effects of C₆₀ molecule on ion channels expressed in smooth muscle cells (SMC). Here we show both computationally and experimentally that water-soluble pristine C₆₀ fullerene strongly inhibits the large conductance Ca²⁺-dependent K⁺ (BK_Ca), but not voltage-gated K⁺ (K_v) channels in pulmonary artery SMC. Both molecular docking simulations and analysis of single channel activity indicate that C₆₀ fullerene blocks BK_Ca channel pore in its open state. In functional tests, C₆₀ fullerene enhanced phenylephrine-induced contraction of pulmonary artery rings by about 25% and reduced endothelium-dependent acetylcholine-induced relaxation by up to 40%. These findings suggest a novel strategy for biomedical application of water-soluble pristine C₆₀ fullerene in vascular dysfunction.

Synthesis and biological activity of 4-amino-3-chloro-1H-pyrrole-2,5-diones

4-Amino-3-chloro-1H-pyrrole-2,5-dione derivatives were designed and synthesized as potential tyrosine kinase inhibitors. One of them has been shown to inhibit growth of cancer cell lines and in vivo tumors. To determine the impact of side groups on biological activity the ability of different 4-amino-3-chloro-1H-pyrrole-2,5-diones to interact with ATP-binding domains of growth factor receptors and with model cell membranes were aimed to be discovered. The methods of molecular docking, short-molecular dynamics (in silico) and non-steady cyclic current-voltage characteristics (in vitro) were used. Five 4-amino-3-chloro-1H-pyrrole-2,5-diones were synthesized from 3,4-dichloro-1H-pyrrole-2,5-diones. All of them demonstrated the potential ability to form complexes with ATP-binding domains of EGFR and VEGFR2. These complexes were more stable compared to those with ANP. 4-Amino-3-chloro-1H-pyrrole-2,5-diones while interact with different bilayer lipid membranes caused an increase of their specific conductance and electric capacity, demonstrating the certain disturbance in lipid packing. Obtained data allowed us to suggest that proposed chemicals can interact with the surface of lipid bilayer, do likely intercalate into the membrane and form stable complexes with EGFR and VEGFR2. So, the prospect of developed chemicals to be effective EGFR and VEGFR2 inhibitors and therefore realize antitumor activity was concluded.

In Silico Target Druggability Assessment: From Structural to Systemic Approaches

This chapter will focus on today's in silico direct and indirect approaches to assess therapeutic target druggability. The direct approach tries to infer from the 3D structure the capacity of the target protein to bind small molecule in order to modulate its biological function. Algorithms to recognize and characterize the quality of the ligand interaction sites whether within buried protein cavities or within large protein-protein interface will be reviewed in the first part of the paper. In the case a ligand-binding site is already identified, indirect aspects of target druggability can be assessed. These indirect approaches focus first on target promiscuity and the potential difficulties in developing specific drugs. It is based on large-scale comparison of protein-binding sites. The second aspect concerns the capacity of the target to induce resistant pathway once it is inhibited or activated by a drug. The emergence of drug-resistant pathways can be assessed through systemic analysis of biological networks implementing metabolism and/or cell regulation signaling.

(Chlorosulfonyl)benzenesulfonyl Fluorides-Versatile Building Blocks for Combinatorial Chemistry: Design, Synthesis and Evaluation of a Covalent Inhibitor Library

Multigram synthesis of (chlorosulfonyl)benzenesulfonyl fluorides is described. Selective modification of these building blocks at the sulfonyl chloride function under parallel synthesis conditions is achieved. It is shown that the reaction scope includes the use of (hetero)aromatic and electron-poor aliphatic amines (e.g., amino nitriles). Utility of the method is demonstrated by preparation of the sulfonyl fluoride library for potential use as covalent fragments, which is demonstrated by a combination of in silico and in vitro screening against trypsin as a model enzyme. As a result, several inhibitors were identified with activity on par with that of the known inhibitor.

C60 fullerene and its nanocomplexes with anticancer drugs modulate circulating phagocyte functions and dramatically increase ROS generation in transformed monocytes

Background

C₆₀ fullerene-based nanoformulations are proposed to have a direct toxic effect on tumor cells. Previous investigations demonstrated that C₆₀ fullerene used alone or being conjugated with chemotherapeutic agents possesses a potent anticancer activity. The main aim of this study was to investigate the effect of C₆₀ fullerene and its nanocomplexes with anticancer drugs on human phagocyte metabolic profile in vitro.

Methods

Analysis of the metabolic profile of phagocytes exposed to C₆₀ fullerene in vitro revealed augmented phagocytic activity and down-regulated reactive nitrogen species generation in these cells. Additionally, cytofluorimetric analysis showed that C₆₀ fullerene can exert direct cytotoxic effect on normal and transformed phagocytes through the vigorous induction of intracellular reactive oxygen species generation.

Results

Cytotoxic action as well as the pro-oxidant effect of C₆₀ fullerene was more pronounced toward malignant phagocytes. At the same time, C₆₀ fullerenes have the ability to down-regulate the pro-oxidant effect of cisplatin on normal cells. These results indicate that C₆₀ fullerenes may influence phagocyte metabolism and have both pro-oxidant and antioxidant properties.

Conclusions

The antineoplastic effect of C₆₀ fullerene has been observed by direct toxic effect on tumor cells, as well as through the modulation of the functions of effector cells of antitumor immunity.

An update on the discovery and development of selective heat shock protein inhibitors as anti-cancer therapy

INTRODUCTION

Over the years, not a single HSP inhibitor has progressed into the post-market phase of drug development despite the success recorded in various pre-clinical and clinical studies. The inability of existing drugs to specifically target oncogenic HSPs has majorly accounted for these setbacks. Recent combinatorial strategies that incorporated computer-aided drug design (CADD) techniques are geared towards the development of highly specific HSP inhibitors with increased activities and minimal toxicities. Areas covered: In this review, strategic therapeutic approaches that have recently aided the development of selective HSP inhibitors were highlighted. Also, the significant contributions of CADD techniques over the years were discussed in detail. This article further describes promising computational paradigms and their applications towards the discovery of highly specific inhibitors of oncogenic HSPs. Expert opinion: The recent shift towards highly selective and specific HSP inhibition has shown great promise as evidenced by the development of paralog/isoform-selective HSP drugs. It could be further augmented with computer-aided drug design strategies, which incorporate reliable methods that would greatly enhance the design and optimization of novel inhibitors with improved activities and minimal toxicities.

Bridging Molecular Docking to Molecular Dynamics in Exploring Ligand-Protein Recognition Process: An Overview

Computational techniques have been applied in the drug discovery pipeline since the 1980s. Given the low computational resources of the time, the first molecular modeling strategies relied on a rigid view of the ligand-target binding process. During the years, the evolution of hardware technologies has gradually allowed simulating the dynamic nature of the binding event. In this work, we present an overview of the evolution of structure-based drug discovery techniques in the study of ligand-target recognition phenomenon, going from the static molecular docking toward enhanced molecular dynamics strategies.

An Old Story in the Parallel Synthesis World: An Approach to Hydantoin Libraries

An approach to the parallel synthesis of hydantoin libraries by reaction of in situ generated 2,2,2-trifluoroethylcarbamates and α-amino esters was developed. To demonstrate utility of the method, a library of 1158 hydantoins designed according to the lead-likeness criteria (MW 200-350, cLogP 1-3) was prepared. The success rate of the method was analyzed as a function of physicochemical parameters of the products, and it was found that the method can be considered as a tool for lead-oriented synthesis. A hydantoin-bearing submicromolar primary hit acting as an Aurora kinase A inhibitor was discovered with a combination of rational design, parallel synthesis using the procedures developed, in silico and in vitro screenings.

Cytotoxic Effects of Dimorfolido-N-Trichloroacetylphosphorylamide and Dimorfolido-N-Benzoylphosphorylamide in Combination with C60 Fullerene on Leukemic Cells and Docking Study of Their Interaction with DNA

Dimorfolido-N-trichloroacetylphosphorylamide (HL1) and dimorfolido-N-benzoylphosphorylamide (HL2) as representatives of carbacylamidophosphates were synthesized and identified by the methods of IR, ¹H, and ³¹P NMR spectroscopy. In vitro HL1 and HL2 at 1 mM concentration caused cell specific and time-dependent decrease of leukemic cell viability. Compounds caused the similar gradual decrease of Jurkat cells viability at 72 h (by 35%). HL1 had earlier and more profound toxic effect as compared to HL2 regardless on leukemic cell line. Viability of Molt-16 and CCRF-CEM cells under the action of HL1 was decreased at 24 h (by 32 and 45%, respectively) with no substantial further reducing up to 72 h. Toxic effect of HL2 was detected only at 72 h of incubation of Jurkat and Molt-16 cells (cell viability was decreased by 40 and 45%, respectively).It was shown that C₆₀ fullerene enhanced the toxic effect of HL2 on leukemic cells. Viability of Jurkat and CCRF-CEM cells at combined action of C₆₀ fullerene and HL2 was decreased at 72 h (by 20 and 24%, respectively) in comparison with the effect of HL2 taken separately.In silico study showed that HL1 and HL2 can interact with DNA and form complexes with DNA both separately and in combination with C₆₀ fullerene. More stable complexes are formed when DNA interacts with HL1 or C₆₀ + HL2 structure. Strong stacking interactions can be formed between HL2 and C₆₀ fullerene. Differences in the types of identified bonds and ways of binding can determine distinction in cytotoxic effects of studied compounds.

Conformational energy range of ligands in protein crystal structures: The difficult quest for accurate understanding

In this review, we address a fundamental question: What is the range of conformational energies seen in ligands in protein-ligand crystal structures? This value is important biophysically, for better understanding the protein-ligand binding process; and practically, for providing a parameter to be used in many computational drug design methods such as docking and pharmacophore searches. We synthesize a selection of previously reported conflicting results from computational studies of this issue and conclude that high ligand conformational energies really are present in some crystal structures. The main source of disagreement between different analyses appears to be due to divergent treatments of electrostatics and solvation. At the same time, however, for many ligands, a high conformational energy is in error, due to either crystal structure inaccuracies or incorrect determination of the reference state. Aside from simple chemistry mistakes, we argue that crystal structure error may mainly be because of the heuristic weighting of ligand stereochemical restraints relative to the fit of the structure to the electron density. This problem cannot be fixed with improvements to electron density fitting or with simple ligand geometry checks, though better metrics are needed for evaluating ligand and binding site chemistry in addition to geometry during structure refinement. The ultimate solution for accurately determining ligand conformational energies lies in ultrahigh-resolution crystal structures that can be refined without restraints.

High-Quality Dataset of Protein-Bound Ligand Conformations and Its Application to Benchmarking Conformer Ensemble Generators

We developed a cheminformatics pipeline for the fully automated selection and extraction of high-quality protein-bound ligand conformations from X-ray structural data. The pipeline evaluates the validity and accuracy of the 3D structures of small molecules according to multiple criteria, including their fit to the electron density and their physicochemical and structural properties. Using this approach, we compiled two high-quality datasets from the Protein Data Bank (PDB): a comprehensive dataset and a diversified subset of 4626 and 2912 structures, respectively. The datasets were applied to benchmarking seven freely available conformer ensemble generators: Balloon (two different algorithms), the RDKit standard conformer ensemble generator, the Experimental-Torsion basic Knowledge Distance Geometry (ETKDG) algorithm, Confab, Frog2 and Multiconf-DOCK. Substantial differences in the performance of the individual algorithms were observed, with RDKit and ETKDG generally achieving a favorable balance of accuracy, ensemble size and runtime. The Platinum datasets are available for download from http://www.zbh.uni-hamburg.de/platinum_dataset .

Octopus: a platform for the virtual high-throughput screening of a pool of compounds against a set of molecular targets

Octopus is an automated workflow management tool that is scalable for virtual high-throughput screening (vHTS). It integrates MOPAC2016, MGLTools, PyMOL, and AutoDock Vina. In contrast to other platforms, Octopus can perform docking simulations of an unlimited number of compounds into a set of molecular targets. After generating the ligands in a drawing package in the Protein Data Bank (PDB) format, Octopus can carry out geometry refinement using the semi-empirical method PM7 implemented in MOPAC2016. Docking simulations can be performed using AutoDock Vina and can utilize the Our Own Molecular Targets (OOMT) databank. Finally, the proposed software compiles the best binding energies into a standard table. Here, we describe two successful case studies that were verified by biological assay. In the first case study, the vHTS process was carried out for 22 (phenylamino)urea derivatives. The vHTS process identified a metalloprotease with the PDB code 1GKC as a molecular target for derivative LE&007. In a biological assay, compound LE&007 was found to inhibit 80% of the activity of this enzyme. In the second case study, compound Tx001 was submitted to the Octopus routine, and the results suggested that Plasmodium falciparum ATP6 (PfATP6) as a molecular target for this compound. Following an antimalarial assay, Tx001 was found to have an inhibitory concentration (IC₅₀) of 8.2 μM against PfATP6. These successful examples illustrate the utility of this software for finding appropriate molecular targets for compounds. Hits can then be identified and optimized as new antineoplastic and antimalarial drugs. Finally, Octopus has a friendly Linux-based user interface, and is available at www.drugdiscovery.com.br . Graphical Abstract Octopus: A platform for inverse virtual screening (IVS) to search new molecular targets for drugs.

Protein-Ligand Docking Methodologies and Its Application in Drug Discovery

Molecular docking is a key tool in structural biology and computer-assisted drug design. Molecular docking is a method which predicts the preferred orientation of a ligand when bound in an active site to form a stable complex. It is the most common method used as a structure-based drug design. Here, the authors intend to discuss the various types of docking methods and their development and applications in modern drug discovery. The important basic theories such as sampling algorithm and scoring functions have been discussed briefly. The performances of the different available docking software have also been discussed. This chapter also includes some application examples of docking studies in modern drug discovery such as targeted drug delivery using carbon nanotubes, docking of nucleic acids to find the binding modes and a comparative study between high-throughput screening and structure-based virtual screening.

Application of Docking Methodologies in QSAR-Based Studies

The computational strategies permeate all aspects of drug discovery such as virtual screening techniques. Virtual screening can be classified into ligand based and structure based methods. The ligand based method such as Quantitative Structure Activity Relationship (QSAR) is used when a set of active ligand compounds is recognized and slight or no structural information is available for the receptors. In structure based drug design, the most widespread method is molecular docking. It is widely accepted that drug activity is obtained through the molecular binding of one ligand to receptor. In their binding conformations, the molecules exhibit geometric and chemical complementarity, both of which are essential for successful drug activity. The molecular docking approach can be used to model the interaction between a small drug molecule and a protein, which allow us to characterize the performance of small molecules in the binding site of target proteins as well as to clarify fundamental biochemical processes.

Molecular Docking at a Glance

The current chapter introduces different aspects of molecular docking technique in order to give an overview to the readers about the topics which will be dealt with throughout this volume. Like many other fields of science, molecular docking studies has experienced a lagging period of slow and steady increase in terms of acquiring attention of scientific community as well as its frequency of application, followed by a pronounced era of exponential expansion in theory, methodology, areas of application and performance due to developments in related technologies such as computational resources and theoretical as well as experimental biophysical methods. In the following sections the evolution of molecular docking will be reviewed and its different components including methods, search algorithms, scoring functions, validation of the methods, and area of applications plus few case studies will be touched briefly.

Discovery and Optimization of 1-Phenoxy-2-aminoindanes as Potent, Selective, and Orally Bioavailable Inhibitors of the Na+/H+ Exchanger Type 3 (NHE3)

The design, synthesis, and structure-activity relationship of 1-phenoxy-2-aminoindanes as inhibitors of the Na⁺/H⁺ exchanger type 3 (NHE3) are described based on a hit from high-throughput screening (HTS). The chemical optimization resulted in the discovery of potent, selective, and orally bioavailable NHE3 inhibitors with 13d as best compound, showing high in vitro permeability and lacking CYP2D6 inhibition as main optimization parameters. Aligning 1-phenoxy-2-aminoindanes onto the X-ray structure of 13d then provided 3D-QSAR models for NHE3 inhibition capturing guidelines for optimization. These models showed good correlation coefficients and allowed for activity estimation. In silico ADMET models for Caco-2 permeability and CYP2D6 inhibition were also successfully applied for this series. Moreover, docking into the CYP2D6 X-ray structure provided a reliable alignment for 3D-QSAR models. Finally 13d, renamed as SAR197, was characterized in vitro and by in vivo pharmacokinetic (PK) and pharmacological studies to unveil its potential for reduction of obstructive sleep apneas.

Polypharmacology in Drug Development: A Minireview of Current Technologies

Polypharmacology, the process in which a single drug is able to bind to multiple targets specifically and simultaneously, is an emerging paradigm in drug development. The potency of a given drug can be increased through the engagement of multiple targets involved in a certain disease. Polypharmacology may also help identify novel applications of existing drugs through drug repositioning. However, many problems and challenges remain in this field. Rather than covering all aspects of polypharmacology, this Minireview is focused primarily on recently reported techniques, from bioinformatics technologies to cheminformatics approaches as well as text-mining-based methods, all of which have made significant contributions to the research of polypharmacology.

Discovery of a Novel, Orally Efficacious Liver X Receptor (LXR) β Agonist

This article describes the application of Contour to the design and discovery of a novel, potent, orally efficacious liver X receptor β (LXRβ) agonist (17). Contour technology is a structure-based drug design platform that generates molecules using a context perceptive growth algorithm guided by a contact sensitive scoring function. The growth engine uses binding site perception and programmable growth capability to create drug-like molecules by assembling fragments that naturally complement hydrophilic and hydrophobic features of the protein binding site. Starting with a crystal structure of LXRβ and a docked 2-(methylsulfonyl)benzyl alcohol fragment (6), Contour was used to design agonists containing a piperazine core. Compound 17 binds to LXRβ with high affinity and to LXRα to a lesser extent, and induces the expression of LXR target genes in vitro and in vivo. This molecule served as a starting point for further optimization and generation of a candidate which is currently in human clinical trials for treating atopic dermatitis.

Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape

Molecular docking is a computational approach for predicting the most probable position of ligands in the binding sites of macromolecules and constitutes the cornerstone of structure-based computer-aided drug design. Here, we present a new algorithm called Attracting Cavities that allows molecular docking to be performed by simple energy minimizations only. The approach consists in transiently replacing the rough potential energy hypersurface of the protein by a smooth attracting potential driving the ligands into protein cavities. The actual protein energy landscape is reintroduced in a second step to refine the ligand position. The scoring function of Attracting Cavities is based on the CHARMM force field and the FACTS solvation model. The approach was tested on the 85 experimental ligand-protein structures included in the Astex diverse set and achieved a success rate of 80% in reproducing the experimental binding mode starting from a completely randomized ligand conformer. The algorithm thus compares favorably with current state-of-the-art docking programs.

4,5-Disubstituted 6-Aryloxy-1,3-dihydrobenzo[c][1,2]oxaboroles Are Broad-Spectrum Serine β-Lactamase Inhibitors

Bacterially expressed β-lactamases are rapidly eroding the clinical utility of the important β-lactam class of antibacterials, significantly impairing our ability to fight serious bacterial infections. This paper describes a study of oxaborole-derived β-lactamase inhibitors in which crystal structures and computational modeling aided in the rational design of analogues with improved spectrum of activity against class A, C, and D enzymes. Crystal structures of two of these inhibitors covalently bound to two different serine β-lactamases, class C Pseudomonas aeruginosa AmpC and class D OXA-10, are described herein. Improved physicochemical properties as well as increased activity against an array of β-lactamases resulted in substantial restoration of susceptibility to ceftazidime in Escherichia coli and Klebsiella pneumoniae.

Receptor-based virtual screening protocol for drug discovery

Computational aided drug design (CADD) is presently a key component in the process of drug discovery and development as it offers great promise to drastically reduce cost and time requirements. In the pharmaceutical arena, virtual screening is normally regarded as the top CADD tool to screen large libraries of chemical structures and reduce them to a key set of likely drug candidates regarding a specific protein target. This chapter provides a comprehensive overview of the receptor-based virtual screening process and of its importance in the present drug discovery and development paradigm. Following a focused contextualization on the subject, the main stages of a virtual screening campaign, including its strengths and limitations, are the subject of particular attention in this review. In all of these stages special consideration will be given to practical issues that are normally the Achilles heel of the virtual screening process.

Panel docking of small-molecule libraries - Prospects to improve efficiency of lead compound discovery

Computational docking as a means to prioritise small molecules in drug discovery projects remains a highly popular in silico screening approach. Contemporary docking approaches without experimental parametrisation can reliably differentiate active and inactive chemotypes in a protein binding site, but the absence of a correlation between the score of a predicted binding pose and the biological activity of the molecule presents a clear limitation. Several novel or improved computational approaches have been developed in the recent past to aid in screening and profiling of small-molecule ligands for drug discovery, but also more broadly in developing conceptual relationships between different protein targets by chemical probing. Among those new methodologies is a strategy known as inverse virtual screening, which involves the docking of a compound into different protein structures. In the present article, we review the different computational screening methodologies that employ docking of atomic models, and, by means of a case study, present an approach that expands the inverse virtual screening concept. By computationally screening a reasonably sized library of 1235 compounds against a panel of 48 mostly human kinases, we have been able to identify five groups of putative lead compounds with substantial diversity when compared to each other. One representative of each of the five groups was synthesised, and tested in kinase inhibition assays, yielding two compounds with micro-molar inhibition in five human kinases. This highly economic and cost-effective methodology holds great promise for drug discovery projects, especially in cases where a group of target proteins share high structural similarity in their binding sites.