Computational approaches to shed light on molecular mechanisms in biological processes

Computational approaches based on Molecular Dynamics simulations, Quantum Mechanical methods and 3D Quantitative Structure-Activity Relationships were employed by computational chemistry groups at the University of Milano-Bicocca to study biological processes at the molecular level. The paper reports the methodologies adopted and the results obtained on Aryl hydrocarbon Receptor and homologous PAS proteins mechanisms, the properties of prion protein peptides, the reaction pathway of hydrogenase and peroxidase enzymes and the defibrillogenic activity of tetracyclines. © Springer-Verlag 2007

The benefits of in silico modeling to identify possible small-molecule drugs and their off-target interactions

Accepted for publication in a future issue of Future Medicinal Chemistry.The research into the use of small molecules as drugs continues to be a key driver in the development of molecular databases, computer-aided drug design software and collaborative platforms. The evolution of computational approaches is driven by the essential criteria that a drug molecule has to fulfill, from the affinity to targets to minimal side effects while having adequate absorption, distribution, metabolism, and excretion (ADME) properties. A combination of ligand- and structure-based drug development approaches is already used to obtain consensus predictions of small molecule activities and their off-target interactions. Further integration of these methods into easy-to-use workflows informed by systems biology could realize the full potential of available data in the drug discovery and reduce the attrition of drug candidates.Peer reviewe

Homology modelling of transferrin-binding protein A from Neisseria meningitidis

Neisseria meningitidis, a causative agent of bacterial meningitis, obtains transferrin-bound iron by expressing two outer membrane located transferrin-binding proteins, TbpA and TbpB. TbpA is thought to be an integral outer membrane pore that facilitates iron uptake. Evidence suggests that TbpA is a useful antigen for inclusion in a vaccine effective against meningococcal disease, hence the identification of regions involved in ligand binding is of paramount importance to design strategies to block uptake of iron. The protein shares sequence and functional similarities to the Escherichia coli siderophore receptors FepA and FhuA, whose structures have been determined. These receptors are composed of two domains, a 22-stranded b-barrel and an N-terminal plug region that sits within the barrel and occludes the transmembrane pore. A three-dimensional TbpA model was constructed using FepA and FhuA structural templates, hydrophobicity analysis and homology modelling. TbpA was found to possess a similar architecture to the siderophore receptors. In addition to providing insights into the highly immunogenic nature of TbpA and allowing the prediction of potentially important ligandbinding epitopes, the model also reveals a narrow channel through its entire length. The relevance of this channel and the spatial arrangement of external loops, to the mechanism of iron translocation employed by TbpA is discussed

Large-scale analysis of influenza A virus nucleoprotein sequence conservation reveals potential drug-target sites

The nucleoprotein (NP) of the influenza A virus encapsidates the viral RNA and participates in the infectious life cycle of the virus. The aims of this study were to find the degree of conservation of NP among all virus subtypes and hosts and to identify conserved binding sites, which may be utilised as potential drug target sites. The analysis of conservation based on 4430 amino acid sequences identified high conservation in known functional regions as well as novel highly conserved sites. Highly variable clusters identified on the surface of NP may be associated with adaptation to different hosts and avoidance of the host immune defence. Ligand binding potential overlapping with high conservation was found in the tail-loop binding site and near the putative RNA binding region. The results provide the basis for developing antivirals that may be universally effective and have a reduced potential to induce resistance through mutations.Peer reviewe

Evolutionary conservation of influenza A PB2 sequences reveals potential target sites for small molecule inhibitors.

The influenza A basic polymerase protein 2 (PB2) functions as part of a heterotrimer to replicate the viral RNA genome. To investigate novel PB2 antiviral target sites, this work identified evolutionary conserved regions across the PB2 protein sequence amongst all sub-types and hosts, as well as ligand binding hot spots which overlap with highly conserved areas. Fifteen binding sites were predicted in different PB2 domains; some of which reside in areas of unknown function. Virtual screening of ~50,000 drug-like compounds showed binding affinities of up to 10.3 kcal/mol. The highest affinity molecules were found to interact with conserved residues including Gln138, Gly222, Ile529, Asn540 and Thr530. A library containing 1738 FDA approved drugs were screened additionally and revealed Paliperidone as a top hit with a binding affinity of -10 kcal/mol. Predicted ligands are ideal leads for new antivirals as they were targeted to evolutionary conserved binding sites

Hot-spot analysis for drug discovery targeting protein-protein interactions

Introduction: Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.This work has been funded by grants BIO2016-79930-R and SEV-2015-0493 from the Spanish Ministry of Economy, Industry and Competitiveness, and grant EFA086/15 from EU Interreg V POCTEFA. M Rosell is supported by an FPI fellowship from the Severo Ochoa program. The authors are grateful for the support of the the Joint BSC-CRG-IRB Programme in Computational Biology.Peer ReviewedPostprint (author's final draft