Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges

Structure-based virtual screening (VS) is a widely used approach that employs the knowledge of the three-dimensional structure of the target of interest in the design of new lead compounds from large-scale molecular docking experiments. Through the prediction of the binding mode and affinity of a small molecule within the binding site of the target of interest, it is possible to understand important properties related to the binding process. Empirical scoring functions are widely used for pose and affinity prediction. Although pose prediction is performed with satisfactory accuracy, the correct prediction of binding affinity is still a challenging task and crucial for the success of structure-based VS experiments. There are several efforts in distinct fronts to develop even more sophisticated and accurate models for filtering and ranking large libraries of compounds. This paper will cover some recent successful applications and methodological advances, including strategies to explore the ligand entropy and solvent effects, training with sophisticated machine-learning techniques, and the use of quantum mechanics. Particular emphasis will be given to the discussion of critical aspects and further directions for the development of more accurate empirical scoring functions

Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment

<p>Abstract</p> <p>Background</p> <p><it>Trypanosoma cruzi </it>is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of <it>Trypanosoma cruzi </it>versus <it>Homo sapiens</it>.</p> <p>Results</p> <p>We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of <it>T</it>. <it>cruzi</it>. In combination with comparative genome analysis to <it>Homo sapiens</it>, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite.</p> <p>Conclusions</p> <p>In this work, we present a set of 397 enzyme models of <it>T</it>. <it>cruzi </it>that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to <it>H. sapiens </it>enzymes, were identified as new potential molecular targets.</p

Performance and parameterization of the algorithm Simplified Generalized Simulated Annealing

The main goal of this study is to find the most effective set of parameters for the Simplified Generalized Simulated Annealing algorithm, SGSA, when applied to distinct cost function as well as to find a possible correlation between the values of these parameters sets and some topological characteristics of the hypersurface of the respective cost function. The SGSA algorithm is an extended and simplified derivative of the GSA algorithm, a Markovian stochastic process based on Tsallis statistics that has been used in many classes of problems, in particular, in biological molecular systems optimization. In all but one of the studied cost functions, the global minimum was found in 100% of the 50 runs. For these functions the best visiting parameter, qV, belongs to the interval [1.2, 1.7]. Also, the temperature decaying parameter, qT, should be increased when better precision is required. Moreover, the similarity in the locus of optimal parameter sets observed in some functions indicates that possibly one could extract topological information about the cost functions from these sets

Multi-and many-objective optimization: present and future in de novo drug design

de novo Drug Design (dnDD) aims to create new molecules that satisfy multiple conflicting objectives. Since several desired properties can be considered in the optimization process, dnDD is naturally categorized as a many-objective optimization problem (ManyOOP), where more than three objectives must be simultaneously optimized. However, a large number of objectives typically pose several challenges that affect the choice and the design of optimization methodologies. Herein, we cover the application of multi- and many-objective optimization methods, particularly those based on Evolutionary Computation and Machine Learning techniques, to enlighten their potential application in dnDD. Additionally, we comprehensively analyze how molecular properties used in the optimization process are applied as either objectives or constraints to the problem. Finally, we discuss future research in many-objective optimization for dnDD, highlighting two important possible impacts: i) its integration with the development of multi-target approaches to accelerate the discovery of innovative and more efficacious drug therapies and ii) its role as a catalyst for new developments in more fundamental and general methodological frameworks in the field

Expedient microwave-assisted synthesis of Bis( n )-lophine analogues as selective butyrylcholinesterase inhibitors: Cytotoxicity evaluation and molecular modelling

In the brain of patients with chronic Alzheimer's disease (AD), the butyrylcholinesterase (BuChE) levels rise while the acetylcholinesterase (AChE) levels decrease. Therefore, development of new selective BuChE inhibitors is of vital importance. Here we present a series of bis(n)-lophine analogues, where two lophine derivatives are connected by a methylene chain. The bis(n)-lophine analogues were synthesized through one-pot four component reaction between pyridinecarboxaldehydes, 1,n-alkanediamines, benzil, and ammonium acetate. The reactions were performed in a microwave reactor in one step for symmetrical bis(n)-lophines, and in two steps for unsymmetrical bis(n)-lophines. The compounds are strongly selective to BuChE, since none of them inhibit AChE. All the compounds, except 7a, 7b and 7c, displayed potent inhibitory activity against BuChE at a micromolar and sub-micromolar range (half maximal inhibitory concentration (IC50) 32.25-0.03 μM). The enzyme kinetic and docking studies suggests that the inhibitor act as a dual binding site inhibitor, binding into the bottom of the gorge and in the peripheral anionic site (PAS) of BuChE cavity. Furthermore, in vitro studies showed that compounds 5b and 12b had no cytotoxic effects in kidney Vero, hepatic HepG2 and C6 astroglial cell lines.Fil: Câmara, Viktor S.. Universidade Federal do Rio Grande do Sul; BrasilFil: Soares, Ana Julia. Universidade Federal do Rio Grande do Sul; BrasilFil: Biscussi, Brunella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Murray, Ana Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Guedes, Isabella A.. Laboratório Nacional de Computação Científica; BrasilFil: Dardenne, Laurent E.. Laboratório Nacional de Computação Científica; BrasilFil: Ruaro, Thaís C.. Universidade Federal do Rio Grande do Sul; BrasilFil: Zimmer, Aline R.. Universidade Federal do Rio Grande do Sul; BrasilFil: Ceschi, Marco A.. Universidade Federal do Rio Grande do Sul; Brasi

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

A Genetic Algorithm for the Ligand-Protein Docking Problem

We analyzed the performance of a real coded &quot;steady-state&quot; genetic algorithm (SSGA) using a grid-based methodology in docking five HIV-1 protease-ligand complexes having known three-dimensional structures. All ligands tested are highly flexible, having more than 10 conformational degrees of freedom. The SSGA was tested for the rigid and flexible ligand docking cases. The implemented genetic algorithm was able to dock successfully rigid and flexible ligand molecules, but with a decreasing performance when the number of ligand conformational degrees of freedom increased. The docked lowest-energy structures have root mean square deviation (RMSD) with respect to the corresponding experimental crystallographic structure ranging from 0.037 to 0.090 in the rigid docking, and 0.420 to 1.943 in the flexible docking. We found that not only the number of ligand conformational degrees of freedom is an important aspect to the algorithm performance, but also that the more internal dihedral angles are critical. Furthermore, our results showed that the initial population distribution can be relevant for the algorithm performance