Cherqaoui Driss - Profil du chercheur

Informations du chercheur

Nom complet

Cherqaoui Driss

Grade

PES

Spécialité

Chimie organique

Thématique de recherche

Synthèse organique et modélisation moléculaire

Laboratoire

Laboratoire de Chimie Moléculaire

Établissement

Faculté des Sciences Semlalia Marrakech

Ouvrages (0 au total)

Aucun ouvrage disponible.

Projets (1 au total)

Modélisation moléculaire : Contribution à la conception d’inhibiteurs du VIH

Type: Non spécifié

Début: 01/01/2017

Fin: 30/12/2018

Organisme financeur:

Agence Universitaire de la Francophonie” and the Scientific Research Fund of Bulgaria. under project DNTS/FrPh01/1.

Publications (29 au total)

Prediction of predominant configuration in enantioselective reduction of -Ketoacid derivatives with baker’s yeast using neural networks

Auteur: Didier Villemin, Driss Cherqaoui, Abdelhalim Mesbah

Revue: European Chemical Bulletin

Année: 2016

The Hyperconjugation and the Trans Bent Structure of A =A (A =C, Si,..., Pb) Double Bond, from Dimetallene A 2 H 4 to Nanosystems

Auteur: Hasna Choukri, Hassan Chataoui, Driss Cherqaoui, Abdellah Jarid

Revue: Silicon

Année: 2015

DOI: 10.1007/s12633-015-9285-8

« Précédent 2 3 4

Communications (22 au total)

Combined singular value decomposition and linear regression methods in QSAR modelling: a case study for predicting HIV-1 and HCV biological activities

Manifestation: International Congress of &bdquo;Apollonia” University from Iași By promoting excellence, we prepare the future Edition XXXI

Date: 2021-03-01

Organisation: IAȘI, ROMANIA

Impact assessment of singular value decomposition linear regression model on QSAR modelling: A case study for predicting HIV-1 and HCV biological activities.

Manifestation: Computational Methods in Toxicology and Pharmacology Integrating Internet Resources (CMTPI-2019)

Date: 2019-06-23

Organisation: Ioannina, Greece.

Tracing Potential Covalent Inhibitors of an E3 Ubiquitin Ligase through Target-Focused Modelling

Manifestation: 2nd MMCS - Facing Novel Challenges in Drug Discovery

Date: 2019-05-15

Organisation: Barcelona, Spain

Molecular modeling: Application of Artificial Neural Networks, Support Vector Machines and Decision Trees for anti HIV activity prediction of organic compounds

Manifestation: 5th International Conference on Computation for Science and Technology (ICCST 2018)

Date: 2018-09-23

Organisation: Antalya Turkey

QSAR models for assessment of the potential of azaindole analogs as HIV-1 attachment inhibitors

Manifestation: 25th Congress of the Society of Chemists and Technologists of Macedonia (SCTM)

Date: 2018-09-19

Organisation: Ohrid Macedonia

Molecular docking study to understand the binding mechanism of HIV-1 attachment inhibitors

Manifestation: The 3rd Forum of scientific research

Date: 2018-05-11

Organisation: Marrakech, Morocco

Binding energy-based approaches to enhance virtual screening in drug discovery workflows

Manifestation: International Conference on Drug Discovery: Biotechnology and Pharma at Cross Roads

Date: 2018-02-15

Organisation: Patiala-India

SAR Studies for the in-silico Prediction of HIV-1 Inhibitors

Manifestation: 3rd International Electronic Conference on Medicinal Chemistry

Date: 2017-11-01

Organisation: Online

Hydrocarbures et clusters des éléments du groupe 13, Analyse énergétiques et considérations écologiques

Manifestation: International Conference on theoretical chemistry and Modeling

Date: 2017-06-15

Organisation: Kenitra, Morocco. March 15-17, (2017).

« Précédent 1 2 3 Suivant »

Thèses (3 au total)

In Silico Drug Design of Potent SARS-CoV-2 Inhibitors

Auteur: Mehdi OUBAHMANE

Directeur: Cherqaoui Driss

Soutenance: 2023

Molecular Modeling: QSAR Studies on Reverse Transcriptase and Gp120 HIV-1 and NS4B HCV Inhibitors

Auteur: HDOUFANE Ismail

Directeur: Cherqaoui Driss

Soutenance: 2021

Targeting Protein Degradation as a Potential and Emerging Therapeutic Approach in Cancer Drug Discovery: Combinatorial In Silico Modeling to Explore the Covalent & Non-covalent Inhibition of Nedd4-1 E3 Ubiquitin Ligase

Auteur: BJIJ Imane

Directeur: Cherqaoui Driss

Soutenance: 2019

Informations du chercheur

Nom complet

Grade

Spécialité

Thématique de recherche

Laboratoire

Établissement

Ouvrages (0 au total)

Projets (1 au total)

Mod&eacute;lisation mol&eacute;culaire : Contribution &agrave; la conception d&rsquo;inhibiteurs du VIH

Publications (29 au total)

Prediction of predominant configuration in enantioselective reduction of -Ketoacid derivatives with baker&rsquo;s yeast using neural networks

The Hyperconjugation and the Trans Bent Structure of A =A (A =C, Si,..., Pb) Double Bond, from Dimetallene A 2 H 4 to Nanosystems

Communications (22 au total)

Combined singular value decomposition and linear regression methods in QSAR modelling: a case study for predicting HIV-1 and HCV biological activities

Impact assessment of singular value decomposition linear regression model on QSAR modelling: A case study for predicting HIV-1 and HCV biological activities.

Tracing Potential Covalent Inhibitors of an E3 Ubiquitin Ligase through Target-Focused Modelling

Molecular modeling: Application of Artificial Neural Networks, Support Vector Machines and Decision Trees for anti HIV activity prediction of organic compounds

QSAR models for assessment of the potential of azaindole analogs as HIV-1 attachment inhibitors

Molecular docking study to understand the binding mechanism of HIV-1 attachment inhibitors

Binding energy-based approaches to enhance virtual screening in drug discovery workflows

SAR Studies for the in-silico Prediction of HIV-1 Inhibitors

Hydrocarbures et clusters des &eacute;l&eacute;ments du groupe 13, Analyse &eacute;nerg&eacute;tiques et consid&eacute;rations &eacute;cologiques

Thèses (3 au total)

In Silico Drug Design of Potent SARS-CoV-2 Inhibitors

Molecular Modeling: QSAR Studies on Reverse Transcriptase and Gp120 HIV-1 and NS4B HCV Inhibitors

Targeting Protein Degradation as a Potential and Emerging Therapeutic Approach in Cancer Drug Discovery: Combinatorial In Silico Modeling to Explore the Covalent &amp; Non-covalent Inhibition of Nedd4-1 E3 Ubiquitin Ligase

Modélisation moléculaire : Contribution à la conception d’inhibiteurs du VIH

Prediction of predominant configuration in enantioselective reduction of -Ketoacid derivatives with baker’s yeast using neural networks

Hydrocarbures et clusters des éléments du groupe 13, Analyse énergétiques et considérations écologiques

Targeting Protein Degradation as a Potential and Emerging Therapeutic Approach in Cancer Drug Discovery: Combinatorial In Silico Modeling to Explore the Covalent & Non-covalent Inhibition of Nedd4-1 E3 Ubiquitin Ligase