Leticia Manen-Freixa

@idibell.cat

ProCure, Oncobell
IDIBELL

Dr. Leticia Manen-Freixa currently holds the position of R&D Scientist in Cheminformatics & Drug Design at IDIBELL, where she also serves as the Computational Lab Manager. This role has provided her with an invaluable opportunity to specialize in a diverse range of areas of Drug Discovery in the oncology R&D field, including polypharmacology, off-target prediction, and the design of antineoplastic drugs. Beyond this, she has delved into the world of artificial intelligence, with a keen focus on Machine Learning, Deep Learning, and NLP. She obtained her PhD in Chemistry and Chemical Engineering from Universitat Ramon Llull in 2022. Her thesis project was positioned in the field of medicinal chemistry, and due to her significant contributions, her profile could be interdisciplinarily described both as a chemoinformatic and organic chemist. She holds a Degree in Chemistry, a MSc in Teacher Training for Secondary School, and a MSc in Pharmaceutical Chemistry.

EDUCATION

PhD in Chemistry & Chemical Engineering (IQS School of Engineering - URL) 2018-2022
Master’s Degree in Pharmaceutical Chemistry (IQS School of Engineering - URL) 2017-2018
Master’s Degree in Formation Of Tearchers For Secondary School (UNIR) 2017-2018
Bachelor of Science: Chemistry (IQS School of Engineering - URL) 2012-2016

RESEARCH, TEACHING, or OTHER INTERESTS

Chemistry, Organic Chemistry, Drug Discovery, Pharmaceutical Science

Scopus Publications

Scholar Citations

Scholar h-index

Scopus Publications

Exploring the unexplored chemical space: Rational identification of new Tafenoquine analogs with antimalarial properties
Leticia Manen-Freixa, Sonia Moliner-Cubel, Francisco-Javier Gamo, Benigno Crespo, José I. Borrell, Jordi Teixidó, and Roger Estrada-Tejedor
Elsevier BV

Short-term exposure to environmental levels of nicotine and cotinine impairs visual motor response in zebrafish larvae through a similar mode of action: Exploring the potential role of zebrafish α7 nAChR
Marina Bellot, Leticia Manen-Freixa, Eva Prats, Juliette Bedrossiantz, Carlos Barata, Cristian Gómez-Canela, Albert A. Antolin, and Demetrio Raldúa
Elsevier BV

Polypharmacology prediction: the long road toward comprehensively anticipating small-molecule selectivity to de-risk drug discovery
Leticia Manen-Freixa and Albert A. Antolin
Informa UK Limited
INTRODUCTION Small molecules often bind to multiple targets, a behavior termed polypharmacology. Anticipating polypharmacology is essential for drug discovery since unknown off-targets can modulate safety and efficacy - profoundly affecting drug discovery success. Unfortunately, experimental methods to assess selectivity present significant limitations and drugs still fail in the clinic due to unanticipated off-targets. Computational methods are a cost-effective, complementary approach to predict polypharmacology. AREAS COVERED This review aims to provide a comprehensive overview of the state of polypharmacology prediction and discuss its strengths and limitations, covering both classical cheminformatics methods and bioinformatic approaches. The authors review available data sources, paying close attention to their different coverage. The authors then discuss major algorithms grouped by the types of data that they exploit using selected examples. EXPERT OPINION Polypharmacology prediction has made impressive progress over the last decades and contributed to identify many off-targets. However, data incompleteness currently limits most approaches to comprehensively predict selectivity. Moreover, our limited agreement on model assessment challenges the identification of the best algorithms - which at present show modest performance in prospective real-world applications. Despite these limitations, the exponential increase of multidisciplinary Big Data and AI hold much potential to better polypharmacology prediction and de-risk drug discovery.

Deconstructing Markush: Improving the R&D Efficiency Using Library Selection in Early Drug Discovery
Leticia Manen-Freixa, José I. Borrell, Jordi Teixidó, and Roger Estrada-Tejedor
MDPI AG
Most of the product patents claim a large number of compounds based on a Markush structure. However, the identification and optimization of new principal active ingredients is frequently driven by a simple Free Wilson approach, leading to a highly focused study only involving the chemical space nearby a hit compound. This fact raises the question: do the tested compounds described in patents really reflect the full molecular diversity described in the Markush structure? In this study, we contrast the performance of rational selection to conventional approaches in seven real-case patents, assessing their ability to describe the patent’s chemical space. Results demonstrate that the integration of computer-aided library selection methods in the early stages of the drug discovery process would boost the identification of new potential hits across the chemical space.

RECENT SCHOLAR PUBLICATIONS

Polypharmacology prediction: the long road toward comprehensively anticipating small-molecule selectivity to de-risk drug discovery
L Manen-Freixa, AA Antolin
Expert Opinion on Drug Discovery 19 (9), 1043-1069 2024

Exploring the unexplored chemical space: Rational identification of new Tafenoquine analogs with antimalarial properties
L Manen-Freixa, S Moliner-Cubel, FJ Gamo, B Crespo, JI Borrell, ...
Bioorganic Chemistry 148, 107472 2024

Short-term exposure to environmental levels of nicotine and cotinine impairs visual motor response in zebrafish larvae through a similar mode of action: Exploring the potential
M Bellot, L Manen-Freixa, E Prats, J Bedrossiantz, C Barata, ...
Science of the Total Environment 912, 169301 2024

Exploring Molecular Diversity: There is Plenty of Room at Markush's
L Mann Freixa
Universitat Ramon Llull 2022

Deconstructing Markush: improving the R&D efficiency using library selection in early drug discovery
L Manen-Freixa, JI Borrell, J Teixid, R Estrada-Tejedor
Pharmaceuticals 15 (9), 1159 2022

Exploring the Unexplored Tafenoquine's Chemical Space: Rational Identification of New Tafenoquine Analogues with Antimalarial Properties
L Manen-Freixa, S Moliner-Cubel, FJ Gamo, B Crespo, JI Borrell, ...
Available at SSRN 4773572

MOST CITED SCHOLAR PUBLICATIONS

Short-term exposure to environmental levels of nicotine and cotinine impairs visual motor response in zebrafish larvae through a similar mode of action: Exploring the potential
M Bellot, L Manen-Freixa, E Prats, J Bedrossiantz, C Barata, ...
Science of the Total Environment 912, 169301 2024
Citations: 6

Deconstructing Markush: improving the R&D efficiency using library selection in early drug discovery
L Manen-Freixa, JI Borrell, J Teixid, R Estrada-Tejedor
Pharmaceuticals 15 (9), 1159 2022
Citations: 3