G. I. Nikolaev

发表

Structural Materials in Shipbuilding and National Economy

I. V. Gorynin, G. I. Nikolaev, 1991 .

Improvement of molds for six-strand radial continuous billet casters

A. S. Kostin, A. K. Belitchenko, G. I. Nikolaev, 1991 .

In Silico Identification of Novel Aromatic Compounds as Potential HIV-1 Entry Inhibitors Mimicking Cellular Receptor CD4

G. I. Nikolaev, Yuri V. Kornoushenko, A. Tuzikov, 2019, Viruses.

Click chemistry in silico, docking, quantum chemical calculations, and molecular dynamics simulations to identify novel 1,2,4-triazole-based compounds as potential aromatase inhibitors

G. I. Nikolaev, Yuri V. Kornoushenko, A. Andrianov, 2019, SN Applied Sciences.

In silico Identification of High-Affinity Ligands of the Hiv-1 Gp120 Protein, Potential Peptidomimetics of Neutralizing Antibody N6

G. I. Nikolaev, Yuri V. Kornoushenko, A. Tuzikov, 2019, Mathematical Biology and Bioinformatics.

Development of Potential HIV-1 Inhibitors by In Silico Click Chemistry And Molecular Modeling Methods

G. I. Nikolaev, I. A. Kashyn, A. Tuzikov, 2018, Mathematical Biology and Bioinformatics.

State of development of optical spectral methods of investigation of metal vaporization. Survey

G. I. Nikolaev, A. M. Nemets, 1978 .

Effectiveness of element utilization in atomic adsorption analysis with the graphite cuvette

G. I. Nikolaev, V. I. Podgornaya, 1974 .

Antifriction carbon plastics in the machinery construction

A. S. Oryshchenko, V. E. Bakhareva, G. I. Nikolaev, 2013, Inorganic Materials: Applied Research.

The improvement of functional features of antifriction polymer composites for sliding friction units

V. E. Bakhareva, G. I. Nikolaev, A. Anisimov, 2010 .

Application of deep learning and molecular modeling to identify small drug-like compounds as potential HIV-1 entry inhibitors

G. I. Nikolaev, N. A. Shuldov, I. P. Bosko, 2021, Journal of biomolecular structure & dynamics.

Development of a Neural Network-Based Approach for Prediction of Potential HIV-1 Entry Inhibitors Using Deep Learning and Molecular Modeling Methods

Alexander V. Tuzikov, Grigory I. Nikolaev, Nikita A. Shuldov, 2020, ISBRA.

Development of a generative adversarial neural network for identification of potential HIV-1 inhibitors by deep learning methods

G. I. Nikolaev, N. A. Shuldov, A. Tuzikov, 2020, Informatics.

Atomic-absorption spectral method for determining the heats of sublimation of high-melting metals

G. I. Nikolaev, A. M. Nemets, 1970 .

On the Antifouling Non-Biocide Coating with Low Surface Energy. Preliminary Results of Testing under Natural Conditions

E. A. Uvarova, G. I. Nikolaev, A. Anisimov, 2020, Inorganic Materials: Applied Research.

Application of the resonance method for determining the elastic and dissipative properties of an orthotropic polymer composite

G. I. Nikolaev, V. S. Ekel’chik, A. Perren, 2009 .

On the Definition of Fire Safety Characteristics for Three-Layer Composite Polymers in Shipbuilding Structures

I. V. Lishevich, A. V. Makhanko, G. I. Nikolaev, 2020, Inorganic Materials: Applied Research.

On the definition of fire-safety characteristics for three-layer composite polymers in shipbuilding structures

I. V. Lishevich, A. V. Makhanko, G. I. Nikolaev, 2020 .

Molecular dynamics for structural complexes of potential HIV-1 inhibitors with the viral envelope gp120 protein

G. I. Nikolaev, I. A. Kashyn, A. Andrianov, 2018, Doklady of the National Academy of Sciences of Belarus.

In Silico Design and Evaluation of Novel Triazole-Based Compounds as Promising Drug Candidates Against Breast Cancer

Grigory I. Nikolaev, Alexander M. Andrianov, G. I. Nikolaev, 2020, ISBRA.

Application of Deep Learning and Molecular Modelling Methods to Identify Potential HIV-1 Entry Inhibitors

A. V. Tuzikov, G. I. Nikolaev, G. I. Nikolaev, 2020 .

Molecular Modeling Of Novel Non-Steroidal Aromatase Inhibitors Containing 1,2,4-Triazole

G. I. Nikolaev, I. A. Kashyn, Yuri V. Kornoushenko, 2018, Mathematical Biology and Bioinformatics.

COMPUTER-AIDED DESIGN OF POTENTIAL AROMATASE INHIBITORS BASED ON 1,2,4-TRIAZOLE DERIVATIVES

G. I. Nikolaev, I. A. Kashyn, Yuri V. Kornoushenko, 2018, Doklady of the National Academy of Sciences of Belarus.