In our lab we are integrated in multidisciplinary projects centered on two major themes for which we established a network of international and national collaborations, both experimental and theoretical. In fact, we lead teams of geographically distributed researchers (Bonn U, Medipol U, Weill Cornell M, Mount Sinai, Utrecht U, IST – Lisbon U, CMAT, INESC and LQAV from Porto U, CNC at UC) with very diverse scientific backgrounds to work at the interface of Computer Science and Structural Biology.

i)    Data-science: Contrary to the reductionist approach aimed at understanding individual components, the new data revolution allows the understanding of complicated interactions and  pathways through the use of statistical Data Mining/Machine-Learning (ML) techniques. This is an active area of research in computer science with the increasing availability of big data collections of all sorts prompting interest in the development of novel tools for data mining. It is expected that continuous improvement of software infrastructure will make ML applicable to a growing range of biological problems. We envision, plan and manage large and completely independent projects that merged knowledge from chemistry, bioinformatics, biophysics, statistics and data-mining to build innovative and completely new methods and computational solutions. Striking examples are the application of ML to a) the detection of Hot-Spots (Protein, 2014, 82;479); b) to the understanding of protein-protein interfacial (PPI) characteristics; c) to the study of co-evolution in PPIs (MOL2NET, 2016, doi:10.3390/mol2net-02-03889); d) to the construction of web-servers such as SBHD (J Chem Info Model, 2015, 55, 1077) and SPOTON (Sci Rep, 2017, 7, 8007); and e) to the application to small-ligand binding IC50 prediction (J Comput Aided Mol Des, 2018, 32, 175). We are now involved in the development of new methodologies to be applied to membrane proteins and drug design.

ii)    Structural modeling: We focused not only in the individual characterization of molecular systems but as well in the development of new and crucial methodologies to tackle specific problems in the area of structural computational biology. In the past we have developed a new methodological approach to calculate the binding free energy upon alanine mutation of residues at a protein-protein interface – compASM (Computational Alanine Scanning Mutagenesis, J Comput Chem, 2007, 28, 644). It has been applied since then very successfully to interfaces in a variety of systems (e.g. MDM2/P53, HEL/antibody FvD1.3, HEL/HyHEL-10, ZipA/FtsZ, IgG1/Streptococcal Protein G) allowing to highlight key features of complex formation.  We compared our approach against Thermodynamic Integration (TI), and our results demonstrated that the much faster compASM protocol gives results at the same level of accuracy as the TI method, but at a fraction of the computational time required to run TI (J Chem Theor Comput, 2013, 9, 1311). We studied in detail the physic-chemical characteristics of the aromatic residues due to their high prevalence as HS at protein-protein interfaces (Biochim Biophys.Acta, 2013, 183, 404). A new VMD plugin was built and is now available for the scientific community (CompASM, Theor Chem Acc, 2012, 131, 1271). We also successfully extended the approach to protein-nucleic acids systems (J Chem Theor Comput, 2013, 9, 4243). Several Solvent Accessible Surface Area (SASA) features were measured and their role in the determination of the binding Hot-Spots statistically evaluated. The combination of these features was also analyzed by a support vector machine learning (SVM) algorithm, which led to an accurate new model for predicting these crucial residues: SBHD (J Chem Info Model, 2015, 55, 1077). More recently we launched a new web-server to predict HS with a very high accuracy and specificity (SPOTON, Sci Rep, 2017, 7, 8007).  

We are also working in PPIs involving G-Protein Coupled Receptors (GPCRs). In our previous research we have contributed to the discovery of asymmetrical signaling through GPCR dimers and determined models for oligomeric GPCRs assemblies (Nature Chem Biol, 2009, 5, 688), produced comprehensive classifications of GPCR/G-protein interfaces that determine subtype selectivity (Biochem Biophys Acta, 2014, 1840, 16), identified functionally critical region on arrestin structure that can be targeted with drugs or chemical tools for functional modulation (ACS Chem Neuro, 2016, 7, 1212–1224) and produced computational protocols to study GPCR function and mechanism (Methods Cell Biol, 2017, 205). Based on this experience and the unprecedented progress in the determination of detailed molecular structures of GPCRs, G-proteins, and members of the Arr family, we are now involved in work that aims to illuminate the molecular mechanisms of signaling selectivity with powerful computational methods by exploring the dynamic properties of the complex systems in their natural environment.

In addition to GPCRs function and molecular mechanism research, we are also working in the design of HIV-based Virus-Like Particles (VLP) that express specific antibodies on the surface as potential target-specific drug/radioactivity delivery platforms to receptors overexpressed in cancer cells, in particular HER2-positive breast cancer cells. We have taken advantage of the newly settled computational methods (Int J Mol Sci, 2016, 27, 17; Sci Rep, 2017, 7, 8007) to study the key interactions of the antibodies with the HIV capsid as well with the receptors. The understanding of the established structural interactions is of fundamental as a guideline to monitor the experimental work paths.

In the area of protein-small ligand interactions, we have been working on various systems: the PICK1 PDZ domain (PNAS, 2010, 107, 413), the nitric oxide synthase isoforms (Chem Biol Drug Design, 2015, 86, 1072), the TEM family of β-lactamases (J Chem Info Model, 2013, 53, 2648) and the Dopamine 2 Receptor. All these studies result from an interchange of ideas with experimental groups in order to develop better and more specific small-molecules.

WEB-server implemented for hot-spots at protein-protein interfaces:
http://milou.science.uu.nl/cgi/services/SPOTON/spoton/

Current Grants:
FCT Programme IF/00578/2014 (Portugal) – Starting package and salary
SurfSara High Computing Center (Netherlands)
Mount Sinai High Computing Center (USA)
H2020-MSCA-IF (Europe)

International collaborations:
Harel Weinstein, Weill Cornell Medicine, USA
Alexandre Bonvin, Utrecht University, Netherlands
Olivier Elemento, Weill Cornell Medicine, USA
Giulia Morra, CNR, Italy
Ozge Sensoy, Istanbul Medipol University, Turkey
Zeynep Gumus, Mount Sinai, USA
Anke Schiedel, Bonn, Germany

National collaborations:
João Galamba-Correia, C2TN, Instituto Superior Técnico
Natália Cordeiro, REQUIMTE, Oporto University
André Melo, REQUIMTE, Oporto University
Vitor Costa, INESC, Oporto University
Joaquim Costa, CMAT, Oporto University

SELECTED PUBLICATIONS

Moreira IS, Koukos P, Melo R, Almeida JG, Preto AJ, Schaarschmidt J, Trellet M, Gumus ZH, Costa J, Bonvin, AMJJ, SpotOne: a web server for prediction of protein-protein binding hot-spots, 2017, Sci Rep, 7(1), 8007, IF= 4.3.

Almeida JG, Preto AJ, Kuokos P, Bonvin AMJJ, Moreira IS, Membrane proteins structure: a review on the major computational tools, 2017, Biochim Biophys Acta, 1859(10), 2021-2039, IF= 3.5.

Melo R, Fieldhouse R, Melo A, Correia JDG, Cordeiro MNDS, Gümüş ZG, Costa J, Bonvin AMJJ, Moreira IS, A Machine-Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces, 2016, Int J Mol Sci, 27, 17(8), IF= 3.3, Citations=6.

Sensoy O, Moreira IS, Morra G, Understanding the differential selectivity of arrestins toward the phosphorylation state of the receptor, 2016, ACS Chemical Neuroscience, 7 (9), 1212-1224, IF= 3.8; Citations=3.

Munteanu CR, Pimenta AC, Fernandez-Lozano C, Melo A, Cordeiro MNDS, Moreira IS. SASA-Based Hot-Spot Detection 2 (SBHD) method for protein-protein and protein-nucleic acid interfaces. J Chem Info Mode., 2015, 55, 1077-86, IF= 3.8, Citations=9.

Moreira IS, Martins JM, Coimbra JTS, Ramos MJ, Fernandes PA, A new scoring function for protein-protein docking that identifies native structures with unprecedented accuracy, Phys Chem Chem Phys,2015, 17, 2378-87, IF= 4.2; Citations=6.

Moreira IS, Structural features of the G-protein/GPCR interactions, Biochim Biophys Acta, 2014, 1840, 16-33, IF= 4.4, Citations=32.

Ramos RM, Moreira IS, Computational alanine scanning mutagenesis – an improved methodological approach for protein-DNA complexes, J Chem Theor Comput. 2013, 9, 4243–4256, IF= 5.3, Citations=7.

Moreira IS, Martins JM, Ramos RM, Fernandes PA, Ramos MJ, Understanding the importance of the aromatic amino-acid residues as hot-spots, Biochim Biophys Acta, 2013, 1834, 404-414, IF= 2.8, Citations=17.

Thorsen TS, Madsen KL, Rebola N, Rathje M, Anggono V, Bach A, Moreira IS, Stuhr-Hansen N, Dyhring T, Peters D, Beuming T, Huganir R, Weinstein HA, Mulle C, Strømgaard K, Ron LC, Gether U, Identification of a small molecule inhibitor of the PICK1 PDZ domain that inhibits hippocampal LTP and LTD – Proc Nat Acad Sci USA, 2010, 107, 413-418, IF= 9.7, Citations=62.

Han Y, Moreira IS, Urizar E., Weinstein H, Javitch J, Asymmetric signaling in GPCR dimers involves allosteric modulation across the interface by activation of the second protomer, Nature Chem Biol, 2009, 5, 688-695, IF= 15.0, Citations=199.

Moreira IS, Fernandes PA, Ramos MJ, Computational Alanine Scanning Mutagenesis – an improved methodological approach, J Comput Chem, 2007, 28, 644-654. IF= 3.3, Citations=115.

Moreira IS, Fernandes PA, Ramos MJ, Hot spots – a detailed review of protein-protein interface determinant amino acid residues, Proteins, 2007, 68: 803-812, IF= 2.5, Citations=360.

CURRICULUM VITAE

Academic Qualification
2008: PhD in Chemistry, Science Faculty, Oporto University, Portugal.
2003: Grad. Diploma in Biochemistry, Science Faculty, Oporto University, Portugal.

Pending Academic Qualifications
2020 [expected]: PhD in Computer Science (currently enrolled in the 1st curricular year), Oporto University, Portugal.
2018 [expected]: Master in Mathematical Engineering (102 out of 120 ECTs concluded), Oporto University, Portugal.
 
Positions             
2015-present: Group Leader (PI, Assistant Professor level) of the Data-Driven Molecular Design Lab at Center for Neuroscience and Cell Biology (CNC), University of Coimbra, Portugal; position awarded under the highly competitive international programme FCT-Investigator for outstanding researchers.
2016-2018: Sabbatical leave at Utrecht University, Netherlands, in A. Bonvin’s Lab, under a H2020 Marie Skłodowska-Curie Fellowship.
2009-2014: Associate Researcher (Assistant Professor level), Science Faculty, Oporto University, Portugal; position awarded under FCT’s international programme “Investigator Ciência 2008” for attracting excellent researchers to Portugal.
2008-2009: Postdoctoral Researcher at Weill Cornell Medical College, NYC, USA; Supervisor: Harel Weinstein.

Fellowships
2016-2018: H2020 – Marie Sklodowska-Curie Individual Fellowship (MSCA-IF(EF))
2015: FCT Individual Postdoctoral Fellowship – Declined in favor of the FCT-Investigator position.
2003-2007: FCT Individual PhD Fellowship – To support the PhD in Chemistry at Oporto University.

Awards
2008: Luso-American Foundation Network Grant (FLAD) – To support the work developed at the Weill Cornell Medicine (USA)
2003: Eng. António de Almeida’s Prize – For the top-ranking student in the Biochemistry Degree.
1998: Excellence Prize – For the top-ranking student in the Secondary School.

Honors
2014: Committee for Professional Opportunities for Women Travel Award – Biophysical Society Meeting, San Francisco, USA.
2006: MGMS Registration Fellowship – Quantum Pharmacology – 30 years on, Oxford, UK.
2006: NBCR Summer Institute Travel and Registration Fellowship – NBCR Summer Institute: Cyberinfrastructure & Multiscale Modeling Approaches”, La Jolla, California.
2006: Marie Curie Travel and Registration Fellowship – CCP5 and Marie Curie Actions: Methods in Molecular Simulation Summer School 2006”, University of Cardiff, Wales.
2006: Italian Physical Society Scholarship – International School of Physics “E. Fermi”, “Protein Folding and Drug Design”, Varenna, Italy.
2006: EMBO Fellowship – “Biomolecular simulation – an EMBO course”, Paris, France.