Jose G. Almeida

SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots

We present SpotOn, a web server to identify and classify interfacial residues as Hot-Spots (HS) and Null-Spots (NS). SpotON implements a robust algorithm with a demonstrated accuracy of 0.95 and sensitivity of 0.98 on an independent test set. The predictor was developed using an ensemble machine learning approach with up-sampling of the minor class. It was trained on 53 complexes using various features, based on both protein 3D structure and sequence. The SpotOn web interface is freely available at: http://milou.science.uu.nl/services/SPOTON/.

Computational Approaches in Antibody-drug Conjugate Optimization for Targeted Cancer Therapy

Cancer has become one of the main leading causes of morbidity and mortality worldwide. One of the critical drawbacks of current cancer therapeutics has been the lack of the target-selectivity, as these drugs should have an effect exclusively on cancer cells while not perturbing healthy ones. In addition, their mechanism of action should be sufficiently fast to avoid the invasion of neighbouring healthy tissues by cancer cells. The use of conventional chemotherapeutic agents and other traditional therapies, such as surgery and radiotherapy, leads to off-target interactions with serious side effects. In this respect, recently developed target-selective Antibody-Drug Conjugates (ADCs) are more effective than traditional therapies, presumably due to their modular structures that combine many chemical properties simultaneously. In particular, ADCs are made up of three different units: a highly selective Monoclonal antibody (Mab) which is developed against a tumour-associated antigen, the payload (cytotoxic agent), and the linker. The latter should be stable in circulation while allowing the release of the cytotoxic agent in target cells. The modular nature of these drugs provides a platform to manipulate and improve selectivity and the toxicity of these molecules independently from each other. This in turn leads to generation of second- and third-generation ADCs, which have been more effective than the previous ones in terms of either selectivity or toxicity or both. Development of ADCs with improved efficacy requires knowledge at the atomic level regarding the structure and dynamics of the molecule. As such, we reviewed all the most recent computational methods used to attain all-atom description of the structure, energetics and dynamics of these systems. In particular, this includes homology modelling, molecular docking and refinement, atomistic and coarse-grained molecular dynamics simulations, principal component and cross-correlation analysis. The full characterization of the structure-activity relationship devoted to ADCs is critical for antibody-drug conjugate research and development.

In Silico Studies Targeting G-protein Coupled Receptors for Drug Research Against Parkinson's Disease.

Parkinson’s Disease (PD) is a long-term neurodegenerative brain disorder that mainly affects the motor system. The causes are still unknown, and even though currently there is no cure, several therapeutic options are available to manage its symptoms. The development of novel anti-parkinsonian agents and an understanding of their proper and optimal use are, indeed, highly demanding. For the last decades, L-3,4-DihydrOxyPhenylAlanine or levodopa (L-DOPA) has been the gold-standard therapy for the symptomatic treatment of motor dysfunctions associated to PD. However, the development of dyskinesias and motor fluctuations (wearing-off and on-off phenomena) associated with long-term L-DOPA replacement therapy have limited its antiparkinsonian efficacy. The investigation for non-dopaminergic therapies has been largely explored as an attempt to counteract the motor side effects associated with dopamine replacement therapy. Being one of the largest cell membrane protein families, G-Protein-Coupled Receptors (GPCRs) have become a relevant target for drug discovery focused on a wide range of therapeutic areas, including Central Nervous System (CNS) diseases. The modulation of specific GPCRs potentially implicated in PD, excluding dopamine receptors, may provide promising non-dopaminergic therapeutic alternatives for symptomatic treatment of PD. In this review, we focused on the impact of specific GPCR subclasses, including dopamine receptors, adenosine receptors, muscarinic acetylcholine receptors, metabotropic glutamate receptors, and 5-hydroxytryptamine receptors, on the pathophysiology of PD and the importance of structure- and ligand-based in silico approaches for the development of small molecules to target these receptors.

An overview of antiretroviral agents for treating HIV infection in paediatric population

Paediatric Acquired ImmunoDeficiency Syndrome (AIDS) is a life-threatening and infectious disease in which the Human Immunodeficiency Virus (HIV) is mainly transmitted through Mother-To-Child Transmission (MTCT) during pregnancy, labour and delivery, or breastfeeding. This review provides an overview of the distinct therapeutic alternatives to abolish the systemic viral replication in paediatric HIV-1 infection. Numerous classes of antiretroviral agents have emerged as therapeutic tools for downregulation of different steps in the HIV replication process. These classes encompass Non-Nucleoside Analogue Reverse Transcriptase Inhibitors (NNRTIs), Nucleoside/Nucleotide Analogue Reverse Transcriptase Inhibitors (NRTIs/NtRTIs), INtegrase Inhibitors (INIs), Protease Inhibitors (PIs), and Entry Inhibitors (EIs). Co-administration of certain antiretroviral drugs with Pharmacokinetic Enhancers (PEs) may boost the effectiveness of the primary therapeutic agent. The combination of multiple antiretroviral drug regimens (Highly Active AntiRetroviral Therapy - HAART) is currently the standard therapeutic approach for HIV infection. So far, the use of HAART offers the best opportunity for prolonged and maximal viral suppression, and preservation of the immune system upon HIV infection. Still, the frequent administration of high doses of multiple drugs, their inefficient ability to reach the viral reservoirs in adequate doses, the development of drug resistance and the lack of patient compliance compromise the complete HIV elimination. The development of nanotechnology-based drug delivery systems may enable targeted delivery of antiretroviral agents to inaccessible viral reservoir sites at therapeutic concentrations. In addition, the application of Computer-Aided Drug Design (CADD) approaches has provided valuable tools for the development of anti-HIV drug candidates with favourable pharmacodynamics and pharmacokinetic properties.

Computational studies of G protein-coupled receptor complexes: Structure and dynamics

G protein-coupled receptors (GPCRs) are ubiquitously expressed transmembrane proteins associated with a wide range of diseases such as Alzheimers, Parkinson, schizophrenia, and also implicated in in several abnormal heart conditions. As such, this family of receptors is regarded as excellent drug targets. However, due to the high number of intracellular signaling partners, these receptors have a complex interaction networks and it becomes challenging to modulate their function. Experimentally determined structures give detailed information on the salient structural properties of these signaling complexes but they are far away from providing mechanistic insights into the underlying process. This chapter presents some of the computational tools, namely molecular dynamics, molecular docking, and molecular modeling and related analyses methods that have been used to complement experimental findings.