Can We Still Trust Docking Results? An Extension of the Applicability of DockBench on PDBbind Database

The number of entries in the Protein Data Bank (PDB) has doubled in the last decade, and it has increased tenfold in the last twenty years. The availability of an ever-growing number of structures is having a huge impact on the Structure-Based Drug Discovery (SBDD), allowing investigation of new targets and giving the possibility to have multiple structures of the same macromolecule in a complex with different ligands. Such a large resource often implies the choice of the most suitable complex for molecular docking calculation, and this task is complicated by the plethora of possible posing and scoring function algorithms available, which may influence the quality of the outcomes. Here, we report a large benchmark performed on the PDBbind database containing more than four thousand entries and seventeen popular docking protocols. We found that, even in protein families wherein docking protocols generally showed acceptable results, certain ligand-protein complexes are poorly reproduced in the self-docking procedure. Such a trend in certain protein families is more pronounced, and this underlines the importance in identification of a suitable protein\ufffdligand conformation coupled to a well-performing docking protocol

Technical and Functional Validation of a Teleoperated Multirobots Platform for Minimally Invasive Surgery

Nowadays Robotic assisted Minimally Invasive Surgeries (R-MIS) are the elective procedures for treating highly accurate and scarcely invasive pathologies, thanks to their abil- ity to empower surgeons\u2019 dexterity and skills. The research on new Multi-Robots Surgery (MRS) platform is cardinal to the development of a new SARAS surgical robotic platform, which aims at carrying out autonomously the assistants tasks during R- MIS procedures. In this work, we will present the SARAS MRS platform validation protocol, framed in order to assess: (i) its technical performances in purely dexterity exercises, and (ii) its functional performances. The results obtained show a prototype able to put the users in the condition of accomplishing the tasks requested (both dexterity- and surgical-related), even with rea- sonably lower performances respect to the industrial standard. The main aspects on which further improvements are needed result to be the stability of the end effectors, the depth per- ception and the vision systems, to be enriched with dedicated virtual fixtures. The SARAS\u2019 aim is to reduce the main surgeon\u2019s workload through the automation of assistive tasks which would benefit both surgeons and patients by facilitating the surgery and reducing the operation time

Novel in silico approaches to depict the protein-ligand recognition events

The discovery and commercialization of a new drug is a long and expensive process. Such process is divided into different phases during which the phisico-chemical and therapeutic properties of the compounds are determined. In particular, the aim of the first phase is to verify whether the compound recognises and interacts efficiently with the target protein. In the last decade, several computational tools have been developed and used to support experimentalists. For this purpose, the scientist have to deal with high complex systems that are difficult to study in whole; thus, the methods and algorithms developers have to strongly simplify the system treatment. Moreover, the time required to obtain the results depends on the computational resources (hardware) available. Fortunately, the technological progress have increased the computing power at low cost, resulting in new and more complex techniques development. During this Ph.D. project we were focused on the development and even the improvement of in silico methods, which allowed to answer certain questions by saving time and money. Furthermore, these methods were implemented in software presenting a Graphical Unit Interface (GUI) with the aim to enhance the user-friendliness. The computational techniques often require a high understanding of the methodology theoretical aspects and also a good informatics proficiency, like different type files handling and hardware management. For this reason, our developed software were organized as pipelines to automatize the entire process and to make this tools useful also for non-expert users. Finally, these methodologies were applied in several research projects demonstrating their usefulness by elucidating, for the first time, interesting aspects of the ligand-protein recognition pathway.La scoperta e la commercializzazione di un nuovo farmaco è un processo lungo e dispendioso, che si articola in diverse fasi durante le quali vengono determinate le proprietà fisiche, chimiche e terapeutiche dei composti investigati. In particolare, nella prima fase di questo processo si cerca di verificare che il composto riconosca e interagisca efficacemente con la proteina bersaglio. A tale scopo, negli ultimi decenni numerosi strumenti computazionali sono stati sviluppati e utilizzati per supportare i ricercatori che si adoperano nella parte sperimentale. I problemi affrontati presentano un alto livello di complessità, che sarebbero difficili da studiare in toto, perciò gli sviluppatori di metodi e algoritmi devono necessariamente adottare notevoli semplificazioni. Inoltre, le risorse di calcolo (hardware) determinano le tempistiche con le quali è possibile ottenere il risultato richiesto. In tal senso, lo sviluppo tecnologico ha portato a un importante aumento della potenza di calcolo a costi accessibili, stimolando l’interesse per lo sviluppo di tecniche sempre più complesse. Durante questo progetto di dottorato ci si è focalizzati sullo sviluppo e il miglioramento di metodi in silico, che permettono di rispondere ad alcuni interrogativei a costi e tempistiche di molto ridotte. Inoltre, tali metodi sono stati implementati in software dotati di interfaccia grafica (GUI) al fine di poter aiutare l’utente nel loro utilizzo. Le tecniche computazionali spesso richiedono un’elevata conoscenza teorica delle metodologie e anche una certa competenza informatica, come la gestione di diversi tipologie di file e delle risorse hardware da impiegare. Per questo motivo i software da noi sviluppati sono stati organizzati in pipelines, in modo da automatizzare l’intero processo e rendere questi strumenti fruibili anhce a persone non esperte. Infine, l’utilità di queste nuove metodologie è stata comprovata in progetti in cui questi strumenti hanno permesso di delucidare aspetti interessanti e fino ad ora non ancora accessibili nell’ambito del riconoscimento proteina-ligando

Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2

Abstract Molecular docking is a powerful tool in the field of computer-aided molecular design. In particular, it is the technique of choice for the prediction of a ligand pose within its target binding site. A multitude of docking methods is available nowadays, whose performance may vary depending on the data set. Therefore, some non-trivial choices should be made before starting a docking simulation. In the same framework, the selection of the target structure to use could be challenging, since the number of available experimental structures is increasing. Both issues have been explored within this work. The pose prediction of a pool of 36 compounds provided by D3R Grand Challenge 2 organizers was preceded by a pipeline to choose the best protein/docking-method couple for each blind ligand. An integrated benchmark approach including ligand shape comparison and cross-docking evaluations was implemented inside our DockBench software. The results are encouraging and show that bringing attention to the choice of the docking simulation fundamental components improves the results of the binding mode predictions

Understanding allosteric interactions in G protein-coupled receptors using Supervised Molecular Dynamics: A prototype study analysing the human A3 adenosine receptor positive allosteric modulator LUF6000

The search for G protein-coupled receptors (GPCRs) allosteric modulators represents an active research field in medicinal chemistry. Allosteric modulators usually exert their activity only in the presence of the orthosteric ligand by binding to protein sites topographically different from the orthosteric cleft. They therefore offer potentially therapeutic advantages by selectively influencing tissue responses only when the endogenous agonist is present. The prediction of putative allosteric site location, however, is a challenging task. In facts, they are usually located in regions showing more structural variation among the family members. In the present work, we applied the recently developed Supervised Molecular Dynamics (SuMD) methodology to interpret at the molecular level the positive allosteric modulation mediated by LUF6000 toward the human adenosine A3 receptor (hA3 AR). Our data suggest at least two possible mechanisms to explain the experimental data available. This study represent, to the best of our knowledge, the first case reported of an allosteric recognition mechanism depicted by means of molecular dynamics simulations

Exploring Protein-Peptide Recognition Pathways Using a Supervised Molecular Dynamics Approach

Peptides have gained increased interest as therapeutic agents during recent years. The high specificity and relatively low toxicity of peptide drugs derive from their extremely tight binding to their targets. Indeed, understanding the molecular mechanism of protein-peptide recognition has important implications in the fields of biology, medicine, and pharmaceutical sciences. Even if crystallography and nuclear magnetic resonance are offering valuable atomic insights into the assembling of the protein-peptide complexes, the mechanism of their recognition and binding events remains largely unclear. In this work we report, for the first time, the use of a supervised molecular dynamics approach to explore the possible protein-peptide binding pathways within a timescale reduced up to three orders of magnitude compared with classical molecular dynamics. The better and faster understating of the protein-peptide recognition pathways could be very beneficial in enlarging the applicability of peptide-based drug design approaches in several biotechnological and pharmaceutical fields

DockBench: An Integrated Informatic Platform Bridging the Gap between the Robust Validation of Docking Protocols and Virtual Screening Simulations

Virtual screening (VS) is a computational methodology that streamlines the drug discovery process by reducing costs and required resources through the in silico identification of potential drug candidates. Structure-based VS (SBVS) exploits knowledge about the three-dimensional (3D) structure of protein targets and uses the docking methodology as search engine for novel hits. The success of a SBVS campaign strongly depends upon the accuracy of the docking protocol used to select the candidates from large chemical libraries. The identification of suitable protocols is therefore a crucial step in the setup of SBVS experiments. Carrying out extensive benchmark studies, however, is usually a tangled task that requires users’ proficiency in handling different file formats and philosophies at the basis of the plethora of existing software packages. We present here DockBench 1.0, a platform available free of charge that eases the pipeline by automating the entire procedure, from docking benchmark to VS setups. In its current implementation, DockBench 1.0 handles seven docking software packages and offers the possibility to test up to seventeen different protocols. The main features of our platform are presented here and the results of the benchmark study of human Checkpoint kinase 1 (hChk1) are discussed as validation test